Science.gov

Sample records for adequate statistical methods

  1. Are shear force methods adequately reported?

    PubMed

    Holman, Benjamin W B; Fowler, Stephanie M; Hopkins, David L

    2016-09-01

    This study aimed to determine the detail to which shear force (SF) protocols and methods have been reported in the scientific literature between 2009 and 2015. Articles (n=734) published in peer-reviewed animal and food science journals and limited to only those testing the SF of unprocessed and non-fabricated mammal meats were evaluated. It was found that most of these SF articles originated in Europe (35.3%), investigated bovine species (49.0%), measured m. longissimus samples (55.2%), used tenderometers manufactured by Instron (31.2%), and equipped with Warner-Bratzler blades (68.8%). SF samples were also predominantly thawed prior to cooking (37.1%) and cooked sous vide, using a water bath (50.5%). Information pertaining to blade crosshead speed (47.5%), recorded SF resistance (56.7%), muscle fibre orientation when tested (49.2%), sub-section or core dimension (21.8%), end-point temperature (29.3%), and other factors contributing to SF variation were often omitted. This base failure diminishes repeatability and accurate SF interpretation, and must therefore be rectified. PMID:27107727

  2. 42 CFR 417.568 - Adequate financial records, statistical data, and cost finding.

    Code of Federal Regulations, 2012 CFR

    2012-10-01

    ... 42 Public Health 3 2012-10-01 2012-10-01 false Adequate financial records, statistical data, and....568 Adequate financial records, statistical data, and cost finding. (a) Maintenance of records. (1) An HMO or CMP must maintain sufficient financial records and statistical data for proper determination...

  3. 42 CFR 417.568 - Adequate financial records, statistical data, and cost finding.

    Code of Federal Regulations, 2013 CFR

    2013-10-01

    ... 42 Public Health 3 2013-10-01 2013-10-01 false Adequate financial records, statistical data, and....568 Adequate financial records, statistical data, and cost finding. (a) Maintenance of records. (1) An HMO or CMP must maintain sufficient financial records and statistical data for proper determination...

  4. 42 CFR 417.568 - Adequate financial records, statistical data, and cost finding.

    Code of Federal Regulations, 2014 CFR

    2014-10-01

    ... 42 Public Health 3 2014-10-01 2014-10-01 false Adequate financial records, statistical data, and....568 Adequate financial records, statistical data, and cost finding. (a) Maintenance of records. (1) An HMO or CMP must maintain sufficient financial records and statistical data for proper determination...

  5. 42 CFR 417.568 - Adequate financial records, statistical data, and cost finding.

    Code of Federal Regulations, 2011 CFR

    2011-10-01

    ... 42 Public Health 3 2011-10-01 2011-10-01 false Adequate financial records, statistical data, and... financial records, statistical data, and cost finding. (a) Maintenance of records. (1) An HMO or CMP must maintain sufficient financial records and statistical data for proper determination of costs payable by...

  6. 42 CFR 417.568 - Adequate financial records, statistical data, and cost finding.

    Code of Federal Regulations, 2010 CFR

    2010-10-01

    ... 42 Public Health 3 2010-10-01 2010-10-01 false Adequate financial records, statistical data, and... financial records, statistical data, and cost finding. (a) Maintenance of records. (1) An HMO or CMP must maintain sufficient financial records and statistical data for proper determination of costs payable by...

  7. AREA OVERLAP METHOD FOR DETERMINING ADEQUATE CHROMATOGRAPHIC RESOLUTION

    EPA Science Inventory

    The Area Overlap method for evaluating analytical chromatograms is evaluated and compared with the Depth-of-the-Valley, IUPAC and Purnell criteria. The method is a resolution criterion based on the fraction of area contributed by an adjacent, overlapping peak. It accounts for bot...

  8. Geopositional Statistical Methods

    NASA Technical Reports Server (NTRS)

    Ross, Kenton

    2006-01-01

    RMSE based methods distort circular error estimates (up to 50% overestimation). The empirical approach is the only statistically unbiased estimator offered. Ager modification to Shultz approach is nearly unbiased, but cumbersome. All methods hover around 20% uncertainty (@ 95% confidence) for low geopositional bias error estimates. This requires careful consideration in assessment of higher accuracy products.

  9. Students' Use of Tutoring Services, by Adequate Yearly Progress Status of School. Statistics in Brief. NCES 2010-023

    ERIC Educational Resources Information Center

    Warkentien, Siri; Grady, Sarah

    2009-01-01

    This Statistics in Brief contributes to current research by investigating the use of tutoring services among a nationally representative group of public school students enrolled in grades K-12. The report compares students in schools that have not made Adequate Yearly Progress (AYP) for 3 or more years, and were thereby enrolled in schools that…

  10. Statistical methods in microbiology.

    PubMed Central

    Ilstrup, D M

    1990-01-01

    Statistical methodology is viewed by the average laboratory scientist, or physician, sometimes with fear and trepidation, occasionally with loathing, and seldom with fondness. Statistics may never be loved by the medical community, but it does not have to be hated by them. It is true that statistical science is sometimes highly mathematical, always philosophical, and occasionally obtuse, but for the majority of medical studies it can be made palatable. The goal of this article has been to outline a finite set of methods of analysis that investigators should choose based on the nature of the variable being studied and the design of the experiment. The reader is encouraged to seek the advice of a professional statistician when there is any doubt about the appropriate method of analysis. A statistician can also help the investigator with problems that have nothing to do with statistical tests, such as quality control, choice of response variable and comparison groups, randomization, and blinding of assessment of response variables. PMID:2200604

  11. Statistical Methods in Cosmology

    NASA Astrophysics Data System (ADS)

    Verde, L.

    2010-03-01

    The advent of large data-set in cosmology has meant that in the past 10 or 20 years our knowledge and understanding of the Universe has changed not only quantitatively but also, and most importantly, qualitatively. Cosmologists rely on data where a host of useful information is enclosed, but is encoded in a non-trivial way. The challenges in extracting this information must be overcome to make the most of a large experimental effort. Even after having converged to a standard cosmological model (the LCDM model) we should keep in mind that this model is described by 10 or more physical parameters and if we want to study deviations from it, the number of parameters is even larger. Dealing with such a high dimensional parameter space and finding parameters constraints is a challenge on itself. Cosmologists want to be able to compare and combine different data sets both for testing for possible disagreements (which could indicate new physics) and for improving parameter determinations. Finally, cosmologists in many cases want to find out, before actually doing the experiment, how much one would be able to learn from it. For all these reasons, sophisiticated statistical techniques are being employed in cosmology, and it has become crucial to know some statistical background to understand recent literature in the field. I will introduce some statistical tools that any cosmologist should know about in order to be able to understand recently published results from the analysis of cosmological data sets. I will not present a complete and rigorous introduction to statistics as there are several good books which are reported in the references. The reader should refer to those.

  12. Explorations in Statistics: Permutation Methods

    ERIC Educational Resources Information Center

    Curran-Everett, Douglas

    2012-01-01

    Learning about statistics is a lot like learning about science: the learning is more meaningful if you can actively explore. This eighth installment of "Explorations in Statistics" explores permutation methods, empiric procedures we can use to assess an experimental result--to test a null hypothesis--when we are reluctant to trust statistical…

  13. Statistical Methods in Psychology Journals.

    ERIC Educational Resources Information Center

    Willkinson, Leland

    1999-01-01

    Proposes guidelines for revising the American Psychological Association (APA) publication manual or other APA materials to clarify the application of statistics in research reports. The guidelines are intended to induce authors and editors to recognize the thoughtless application of statistical methods. Contains 54 references. (SLD)

  14. Statistical Methods for Evolutionary Trees

    PubMed Central

    Edwards, A. W. F.

    2009-01-01

    In 1963 and 1964, L. L. Cavalli-Sforza and A. W. F. Edwards introduced novel methods for computing evolutionary trees from genetical data, initially for human populations from blood-group gene frequencies. The most important development was their introduction of statistical methods of estimation applied to stochastic models of evolution. PMID:19797062

  15. Improved ASTM G72 Test Method for Ensuring Adequate Fuel-to-Oxidizer Ratios

    NASA Technical Reports Server (NTRS)

    Juarez, Alfredo; Harper, Susana A.

    2016-01-01

    The ASTM G72/G72M-15 Standard Test Method for Autogenous Ignition Temperature of Liquids and Solids in a High-Pressure Oxygen-Enriched Environment is currently used to evaluate materials for the ignition susceptibility driven by exposure to external heat in an enriched oxygen environment. Testing performed on highly volatile liquids such as cleaning solvents has proven problematic due to inconsistent test results (non-ignitions). Non-ignition results can be misinterpreted as favorable oxygen compatibility, although they are more likely associated with inadequate fuel-to-oxidizer ratios. Forced evaporation during purging and inadequate sample size were identified as two potential causes for inadequate available sample material during testing. In an effort to maintain adequate fuel-to-oxidizer ratios within the reaction vessel during test, several parameters were considered, including sample size, pretest sample chilling, pretest purging, and test pressure. Tests on a variety of solvents exhibiting a range of volatilities are presented in this paper. A proposed improvement to the standard test protocol as a result of this evaluation is also presented. Execution of the final proposed improved test protocol outlines an incremental step method of determining optimal conditions using increased sample sizes while considering test system safety limits. The proposed improved test method increases confidence in results obtained by utilizing the ASTM G72 autogenous ignition temperature test method and can aid in the oxygen compatibility assessment of highly volatile liquids and other conditions that may lead to false non-ignition results.

  16. A method for determining adequate resistance form of complete cast crown preparations.

    PubMed

    Weed, R M; Baez, R J

    1984-09-01

    A diagram with various degrees of occlusal convergence, which takes into consideration the length and diameter of complete crown preparations, was designed as a guide to assist the dentist to obtain adequate resistance form. To test the validity of the diagram, five groups of complete cast crown stainless steel dies were prepared (3.5 mm long, occlusal convergence 10, 13, 16, 19, and 22 degrees). Gold copings were cast for each of the 50 preparations. Displacement force was applied to the casting perpendicularly to a simulated 30-degree cuspal incline until the casting was displaced. Castings were deformed at margins except for the 22-degree group. Castings from this group were displaced without deformation, and it was concluded that there was a lack of adequate resistance form as predicted by the diagram. The hypothesis that the diagram could be used to predict adequate or inadequate resistance form was confirmed by this study. PMID:6384470

  17. Vortex methods and vortex statistics

    SciTech Connect

    Chorin, A.J.

    1993-05-01

    Vortex methods originated from the observation that in incompressible, inviscid, isentropic flow vorticity (or, more accurately, circulation) is a conserved quantity, as can be readily deduced from the absence of tangential stresses. Thus if the vorticity is known at time t = 0, one can deduce the flow at a later time by simply following it around. In this narrow context, a vortex method is a numerical method that makes use of this observation. Even more generally, the analysis of vortex methods leads, to problems that are closely related to problems in quantum physics and field theory, as well as in harmonic analysis. A broad enough definition of vortex methods ends up by encompassing much of science. Even the purely computational aspects of vortex methods encompass a range of ideas for which vorticity may not be the best unifying theme. The author restricts himself in these lectures to a special class of numerical vortex methods, those that are based on a Lagrangian transport of vorticity in hydrodynamics by smoothed particles (``blobs``) and those whose understanding contributes to the understanding of blob methods. Vortex methods for inviscid flow lead to systems of ordinary differential equations that can be readily clothed in Hamiltonian form, both in three and two space dimensions, and they can preserve exactly a number of invariants of the Euler equations, including topological invariants. Their viscous versions resemble Langevin equations. As a result, they provide a very useful cartoon of statistical hydrodynamics, i.e., of turbulence, one that can to some extent be analyzed analytically and more importantly, explored numerically, with important implications also for superfluids, superconductors, and even polymers. In the authors view, vortex ``blob`` methods provide the most promising path to the understanding of these phenomena.

  18. Recent statistical methods for orientation data

    NASA Technical Reports Server (NTRS)

    Batschelet, E.

    1972-01-01

    The application of statistical methods for determining the areas of animal orientation and navigation are discussed. The method employed is limited to the two-dimensional case. Various tests for determining the validity of the statistical analysis are presented. Mathematical models are included to support the theoretical considerations and tables of data are developed to show the value of information obtained by statistical analysis.

  19. Elementary Science Methods Courses and the "National Science Education Standards": Are We Adequately Preparing Teachers?

    ERIC Educational Resources Information Center

    Smith, Leigh K.; Gess-Newsome, Julie

    2004-01-01

    Despite the apparent lack of universally accepted goals or objectives for elementary science methods courses, teacher educators nationally are autonomously designing these classes to prepare prospective teachers to teach science. It is unclear, however, whether science methods courses are preparing teachers to teach science effectively or to…

  20. Are adequate methods available to detect protist parasites on fresh produce?

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Human parasitic protists such as Cryptosporidium, Giardia and microsporidia contaminate a variety of fresh produce worldwide. Existing detection methods lack sensitivity and specificity for most foodborne parasites. Furthermore, detection has been problematic because these parasites adhere tenacious...

  1. Statistical methods in physical mapping

    SciTech Connect

    Nelson, D.O.

    1995-05-01

    One of the great success stories of modern molecular genetics has been the ability of biologists to isolate and characterize the genes responsible for serious inherited diseases like fragile X syndrome, cystic fibrosis and myotonic muscular dystrophy. This dissertation concentrates on constructing high-resolution physical maps. It demonstrates how probabilistic modeling and statistical analysis can aid molecular geneticists in the tasks of planning, execution, and evaluation of physical maps of chromosomes and large chromosomal regions. The dissertation is divided into six chapters. Chapter 1 provides an introduction to the field of physical mapping, describing the role of physical mapping in gene isolation and ill past efforts at mapping chromosomal regions. The next two chapters review and extend known results on predicting progress in large mapping projects. Such predictions help project planners decide between various approaches and tactics for mapping large regions of the human genome. Chapter 2 shows how probability models have been used in the past to predict progress in mapping projects. Chapter 3 presents new results, based on stationary point process theory, for progress measures for mapping projects based on directed mapping strategies. Chapter 4 describes in detail the construction of all initial high-resolution physical map for human chromosome 19. This chapter introduces the probability and statistical models involved in map construction in the context of a large, ongoing physical mapping project. Chapter 5 concentrates on one such model, the trinomial model. This chapter contains new results on the large-sample behavior of this model, including distributional results, asymptotic moments, and detection error rates. In addition, it contains an optimality result concerning experimental procedures based on the trinomial model. The last chapter explores unsolved problems and describes future work.

  2. Quasi-Isotropic Approximation of Geometrical Optics Method as Adequate Electrodynamical Basis for Tokamak Plasma Polarimetry

    NASA Astrophysics Data System (ADS)

    Bieg, Bohdan; Chrzanowski, Janusz; Kravtsov, Yury A.; Orsitto, Francesco

    Basic principles and recent findings of quasi-isotropic approximation (QIA) of a geometrical optics method are presented in a compact manner. QIA was developed in 1969 to describe electromagnetic waves in weakly anisotropic media. QIA represents the wave field as a power series in two small parameters, one of which is a traditional geometrical optics parameter, equal to wavelength ratio to plasma characteristic scale, and the other one is the largest component of anisotropy tensor. As a result, "" QIA ideally suits to tokamak polarimetry/interferometry systems in submillimeter range, where plasma manifests properties of weakly anisotropic medium.

  3. Statistical methods for nuclear material management

    SciTech Connect

    Bowen W.M.; Bennett, C.A.

    1988-12-01

    This book is intended as a reference manual of statistical methodology for nuclear material management practitioners. It describes statistical methods currently or potentially important in nuclear material management, explains the choice of methods for specific applications, and provides examples of practical applications to nuclear material management problems. Together with the accompanying training manual, which contains fully worked out problems keyed to each chapter, this book can also be used as a textbook for courses in statistical methods for nuclear material management. It should provide increased understanding and guidance to help improve the application of statistical methods to nuclear material management problems.

  4. Statistical methods for environmental pollution monitoring

    SciTech Connect

    Gilbert, R.O.

    1987-01-01

    The application of statistics to environmental pollution monitoring studies requires a knowledge of statistical analysis methods particularly well suited to pollution data. This book fills that need by providing sampling plans, statistical tests, parameter estimation procedure techniques, and references to pertinent publications. Most of the statistical techniques are relatively simple, and examples, exercises, and case studies are provided to illustrate procedures. The book is logically divided into three parts. Chapters 1, 2, and 3 are introductory chapters. Chapters 4 through 10 discuss field sampling designs and Chapters 11 through 18 deal with a broad range of statistical analysis procedures. Some statistical techniques given here are not commonly seen in statistics book. For example, see methods for handling correlated data (Sections 4.5 and 11.12), for detecting hot spots (Chapter 10), and for estimating a confidence interval for the mean of a lognormal distribution (Section 13.2). Also, Appendix B lists a computer code that estimates and tests for trends over time at one or more monitoring stations using nonparametric methods (Chapters 16 and 17). Unfortunately, some important topics could not be included because of their complexity and the need to limit the length of the book. For example, only brief mention could be made of time series analysis using Box-Jenkins methods and of kriging techniques for estimating spatial and spatial-time patterns of pollution, although multiple references on these topics are provided. Also, no discussion of methods for assessing risks from environmental pollution could be included.

  5. A Statistical Method for Syntactic Dialectometry

    ERIC Educational Resources Information Center

    Sanders, Nathan C.

    2010-01-01

    This dissertation establishes the utility and reliability of a statistical distance measure for syntactic dialectometry, expanding dialectometry's methods to include syntax as well as phonology and the lexicon. It establishes the measure's reliability by comparing its results to those of dialectology and phonological dialectometry on Swedish…

  6. Statistical versus nonstatistical temperature inversion methods

    NASA Technical Reports Server (NTRS)

    Smith, W. L.; Fleming, H. E.

    1972-01-01

    Vertical temperature profiles are derived from radiation measurements by inverting the integral equation of radiative transfer. Because of the nonuniqueness of the solution, the particular temperature profile obtained depends on the numerical inversion technique used and the type of auxiliary information incorporated in the solution. The choice of an inversion algorithm depends on many factors; including the speed and size of computer, the availability of representative statistics, and the accuracy of initial data. Results are presented for a numerical study comparing two contrasting inversion methods: the statistical-matrix inversion method and the nonstatistical-iterative method. These were found to be the most applicable to the problem of determining atmospheric temperature profiles. Tradeoffs between the two methods are discussed.

  7. Computational Statistical Methods for Social Network Models

    PubMed Central

    Hunter, David R.; Krivitsky, Pavel N.; Schweinberger, Michael

    2013-01-01

    We review the broad range of recent statistical work in social network models, with emphasis on computational aspects of these methods. Particular focus is applied to exponential-family random graph models (ERGM) and latent variable models for data on complete networks observed at a single time point, though we also briefly review many methods for incompletely observed networks and networks observed at multiple time points. Although we mention far more modeling techniques than we can possibly cover in depth, we provide numerous citations to current literature. We illustrate several of the methods on a small, well-known network dataset, Sampson’s monks, providing code where possible so that these analyses may be duplicated. PMID:23828720

  8. Statistical Methods for Rapid Aerothermal Analysis and Design Technology: Validation

    NASA Technical Reports Server (NTRS)

    DePriest, Douglas; Morgan, Carolyn

    2003-01-01

    The cost and safety goals for NASA s next generation of reusable launch vehicle (RLV) will require that rapid high-fidelity aerothermodynamic design tools be used early in the design cycle. To meet these requirements, it is desirable to identify adequate statistical models that quantify and improve the accuracy, extend the applicability, and enable combined analyses using existing prediction tools. The initial research work focused on establishing suitable candidate models for these purposes. The second phase is focused on assessing the performance of these models to accurately predict the heat rate for a given candidate data set. This validation work compared models and methods that may be useful in predicting the heat rate.

  9. Some useful statistical methods for model validation.

    PubMed Central

    Marcus, A H; Elias, R W

    1998-01-01

    Although formal hypothesis tests provide a convenient framework for displaying the statistical results of empirical comparisons, standard tests should not be used without consideration of underlying measurement error structure. As part of the validation process, predictions of individual blood lead concentrations from models with site-specific input parameters are often compared with blood lead concentrations measured in field studies that also report lead concentrations in environmental media (soil, dust, water, paint) as surrogates for exposure. Measurements of these environmental media are subject to several sources of variability, including temporal and spatial sampling, sample preparation and chemical analysis, and data entry or recording. Adjustments for measurement error must be made before statistical tests can be used to empirically compare environmental data with model predictions. This report illustrates the effect of measurement error correction using a real dataset of child blood lead concentrations for an undisclosed midwestern community. We illustrate both the apparent failure of some standard regression tests and the success of adjustment of such tests for measurement error using the SIMEX (simulation-extrapolation) procedure. This procedure adds simulated measurement error to model predictions and then subtracts the total measurement error, analogous to the method of standard additions used by analytical chemists. Images Figure 1 Figure 3 PMID:9860913

  10. Seasonal UK Drought Forecasting using Statistical Methods

    NASA Astrophysics Data System (ADS)

    Richardson, Doug; Fowler, Hayley; Kilsby, Chris; Serinaldi, Francesco

    2016-04-01

    In the UK drought is a recurrent feature of climate with potentially large impacts on public water supply. Water companies' ability to mitigate the impacts of drought by managing diminishing availability depends on forward planning and it would be extremely valuable to improve forecasts of drought on monthly to seasonal time scales. By focusing on statistical forecasting methods, this research aims to provide techniques that are simpler, faster and computationally cheaper than physically based models. In general, statistical forecasting is done by relating the variable of interest (some hydro-meteorological variable such as rainfall or streamflow, or a drought index) to one or more predictors via some formal dependence. These predictors are generally antecedent values of the response variable or external factors such as teleconnections. A candidate model is Generalised Additive Models for Location, Scale and Shape parameters (GAMLSS). GAMLSS is a very flexible class allowing for more general distribution functions (e.g. highly skewed and/or kurtotic distributions) and the modelling of not just the location parameter but also the scale and shape parameters. Additionally GAMLSS permits the forecasting of an entire distribution, allowing the output to be assessed in probabilistic terms rather than simply the mean and confidence intervals. Exploratory analysis of the relationship between long-memory processes (e.g. large-scale atmospheric circulation patterns, sea surface temperatures and soil moisture content) and drought should result in the identification of suitable predictors to be included in the forecasting model, and further our understanding of the drivers of UK drought.

  11. Quantitative statistical methods for image quality assessment.

    PubMed

    Dutta, Joyita; Ahn, Sangtae; Li, Quanzheng

    2013-01-01

    Quantitative measures of image quality and reliability are critical for both qualitative interpretation and quantitative analysis of medical images. While, in theory, it is possible to analyze reconstructed images by means of Monte Carlo simulations using a large number of noise realizations, the associated computational burden makes this approach impractical. Additionally, this approach is less meaningful in clinical scenarios, where multiple noise realizations are generally unavailable. The practical alternative is to compute closed-form analytical expressions for image quality measures. The objective of this paper is to review statistical analysis techniques that enable us to compute two key metrics: resolution (determined from the local impulse response) and covariance. The underlying methods include fixed-point approaches, which compute these metrics at a fixed point (the unique and stable solution) independent of the iterative algorithm employed, and iteration-based approaches, which yield results that are dependent on the algorithm, initialization, and number of iterations. We also explore extensions of some of these methods to a range of special contexts, including dynamic and motion-compensated image reconstruction. While most of the discussed techniques were developed for emission tomography, the general methods are extensible to other imaging modalities as well. In addition to enabling image characterization, these analysis techniques allow us to control and enhance imaging system performance. We review practical applications where performance improvement is achieved by applying these ideas to the contexts of both hardware (optimizing scanner design) and image reconstruction (designing regularization functions that produce uniform resolution or maximize task-specific figures of merit). PMID:24312148

  12. Quantitative Statistical Methods for Image Quality Assessment

    PubMed Central

    Dutta, Joyita; Ahn, Sangtae; Li, Quanzheng

    2013-01-01

    Quantitative measures of image quality and reliability are critical for both qualitative interpretation and quantitative analysis of medical images. While, in theory, it is possible to analyze reconstructed images by means of Monte Carlo simulations using a large number of noise realizations, the associated computational burden makes this approach impractical. Additionally, this approach is less meaningful in clinical scenarios, where multiple noise realizations are generally unavailable. The practical alternative is to compute closed-form analytical expressions for image quality measures. The objective of this paper is to review statistical analysis techniques that enable us to compute two key metrics: resolution (determined from the local impulse response) and covariance. The underlying methods include fixed-point approaches, which compute these metrics at a fixed point (the unique and stable solution) independent of the iterative algorithm employed, and iteration-based approaches, which yield results that are dependent on the algorithm, initialization, and number of iterations. We also explore extensions of some of these methods to a range of special contexts, including dynamic and motion-compensated image reconstruction. While most of the discussed techniques were developed for emission tomography, the general methods are extensible to other imaging modalities as well. In addition to enabling image characterization, these analysis techniques allow us to control and enhance imaging system performance. We review practical applications where performance improvement is achieved by applying these ideas to the contexts of both hardware (optimizing scanner design) and image reconstruction (designing regularization functions that produce uniform resolution or maximize task-specific figures of merit). PMID:24312148

  13. Are the defined substrate-based methods adequate to determine the microbiological quality of natural recreational waters?

    PubMed

    Valente, Marta Sofia; Pedro, Paulo; Alonso, M Carmen; Borrego, Juan J; Dionísio, Lídia

    2010-03-01

    Monitoring the microbiological quality of water used for recreational activities is very important to human public health. Although the sanitary quality of recreational marine waters could be evaluated by standard methods, they are time-consuming and need confirmation. For these reasons, faster and more sensitive methods, such as the defined substrate-based technology, have been developed. In the present work, we have compared the standard method of membrane filtration using Tergitol-TTC agar for total coliforms and Escherichia coli, and Slanetz and Bartley agar for enterococci, and the IDEXX defined substrate technology for these faecal pollution indicators to determine the microbiological quality of natural recreational waters. ISO 17994:2004 standard was used to compare these methods. The IDEXX for total coliforms and E. coli, Colilert, showed higher values than those obtained by the standard method. Enterolert test, for the enumeration of enterococci, showed lower values when compared with the standard method. It may be concluded that more studies to evaluate the precision and accuracy of the rapid tests are required in order to apply them for routine monitoring of marine and freshwater recreational bathing areas. The main advantages of these methods are that they are more specific, feasible and simpler than the standard methodology. PMID:20009243

  14. A new method for derivation of statistical weight of the Gentile Statistics

    NASA Astrophysics Data System (ADS)

    Selvi, Sevilay; Uncu, Haydar

    2015-10-01

    We present a new method for obtaining the statistical weight of the Gentile Statistics. In a recent paper, Perez and Tun presented an approximate combinatoric and an exact recursive formula for the statistical weight of Gentile Statistics, beginning from bosonic and fermionic cases, respectively Hernandez-Perez and Tun (2007). In this paper, we obtain two exact, one combinatoric and one recursive, formulae for the statistical weight of Gentile Statistics, by another approach. The combinatoric formula is valid only for special cases, whereas recursive formula is valid for all possible cases. Moreover, for a given q-maximum number of particles that can occupy a level for Gentile statistics-the recursive formula we have derived gives the result much faster than the recursive formula presented in Hernandez-Perez and Tun (2007), when one uses a computer program. Moreover we obtained the statistical weight for the distribution proposed by Dai and Xie (2009).

  15. Statistical methods of estimating mining costs

    USGS Publications Warehouse

    Long, K.R.

    2011-01-01

    Until it was defunded in 1995, the U.S. Bureau of Mines maintained a Cost Estimating System (CES) for prefeasibility-type economic evaluations of mineral deposits and estimating costs at producing and non-producing mines. This system had a significant role in mineral resource assessments to estimate costs of developing and operating known mineral deposits and predicted undiscovered deposits. For legal reasons, the U.S. Geological Survey cannot update and maintain CES. Instead, statistical tools are under development to estimate mining costs from basic properties of mineral deposits such as tonnage, grade, mineralogy, depth, strip ratio, distance from infrastructure, rock strength, and work index. The first step was to reestimate "Taylor's Rule" which relates operating rate to available ore tonnage. The second step was to estimate statistical models of capital and operating costs for open pit porphyry copper mines with flotation concentrators. For a sample of 27 proposed porphyry copper projects, capital costs can be estimated from three variables: mineral processing rate, strip ratio, and distance from nearest railroad before mine construction began. Of all the variables tested, operating costs were found to be significantly correlated only with strip ratio.

  16. Uncertainty analysis of statistical downscaling methods

    NASA Astrophysics Data System (ADS)

    Khan, Mohammad Sajjad; Coulibaly, Paulin; Dibike, Yonas

    2006-03-01

    Three downscaling models namely Statistical Down-Scaling Model (SDSM), Long Ashton Research Station Weather Generator (LARS-WG) model and Artificial Neural Network (ANN) model have been compared in terms various uncertainty assessments exhibited in their downscaled results of daily precipitation, daily maximum and minimum temperatures. In case of daily maximum and minimum temperature, uncertainty is assessed by comparing monthly mean and variance of downscaled and observed daily maximum and minimum temperature at each month of the year at 95% confidence level. In addition, uncertainties of the monthly means and variances of downscaled daily temperature have been calculated using 95% confidence intervals, which are compared with the observed uncertainties of means and variances. In daily precipitation downscaling, in addition to comparing means and variances, uncertainties have been assessed by comparing monthly mean dry and wet spell lengths and their confidence intervals, cumulative frequency distributions (cdfs) of monthly mean of daily precipitation, and the distributions of monthly wet and dry days for observed and downscaled daily precipitation. The study has been carried out using 40 years of observed and downscaled daily precipitation, daily maximum and minimum temperature data using NCEP (National Center for Environmental Prediction) reanalysis predictors starting from 1961 to 2000. The uncertainty assessment results indicate that the SDSM is the most capable of reproducing various statistical characteristics of observed data in its downscaled results with 95% confidence level, the ANN is the least capable in this respect, and the LARS-WG is in between SDSM and ANN.

  17. Statistical Methods Used in Gifted Education Journals, 2006-2010

    ERIC Educational Resources Information Center

    Warne, Russell T.; Lazo, Maria; Ramos, Tammy; Ritter, Nicola

    2012-01-01

    This article describes the statistical methods used in quantitative and mixed methods articles between 2006 and 2010 in five gifted education research journals. Results indicate that the most commonly used statistical methods are means (85.9% of articles), standard deviations (77.8%), Pearson's "r" (47.8%), X[superscript 2] (32.2%), ANOVA (30.7%),…

  18. Problems of applicability of statistical methods in cosmology

    SciTech Connect

    Levin, S. F.

    2015-12-15

    The problems arising from the incorrect formulation of measuring problems of identification for cosmological models and violations of conditions of applicability of statistical methods are considered.

  19. Cratering statistics on asteroids: Methods and perspectives

    NASA Astrophysics Data System (ADS)

    Chapman, C.

    2014-07-01

    Crater size-frequency distributions (SFDs) on the surfaces of solid-surfaced bodies in the solar system have provided valuable insights about planetary surface processes and about impactor populations since the first spacecraft images were obtained in the 1960s. They can be used to determine relative age differences between surficial units, to obtain absolute model ages if the impactor flux and scaling laws are understood, to assess various endogenic planetary or asteroidal processes that degrade craters or resurface units, as well as assess changes in impactor populations across the solar system and/or with time. The first asteroid SFDs were measured from Galileo images of Gaspra and Ida (cf., Chapman 2002). Despite the superficial simplicity of these studies, they are fraught with many difficulties, including confusion by secondary and/or endogenic cratering and poorly understood aspects of varying target properties (including regoliths, ejecta blankets, and nearly-zero-g rubble piles), widely varying attributes of impactors, and a host of methodological problems including recognizability of degraded craters, which is affected by illumination angle and by the ''personal equations'' of analysts. Indeed, controlled studies (Robbins et al. 2014) demonstrate crater-density differences of a factor of two or more between experienced crater counters. These inherent difficulties have been especially apparent in divergent results for Vesta from different members of the Dawn Science Team (cf. Russell et al. 2013). Indeed, they have been exacerbated by misuse of a widely available tool (Craterstats: hrscview.fu- berlin.de/craterstats.html), which incorrectly computes error bars for proper interpretation of cumulative SFDs, resulting in derived model ages specified to three significant figures and interpretations of statistically insignificant kinks. They are further exacerbated, and for other small-body crater SFDs analyzed by the Berlin group, by stubbornly adopting

  20. Online Statistics Labs in MSW Research Methods Courses: Reducing Reluctance toward Statistics

    ERIC Educational Resources Information Center

    Elliott, William; Choi, Eunhee; Friedline, Terri

    2013-01-01

    This article presents results from an evaluation of an online statistics lab as part of a foundations research methods course for master's-level social work students. The article discusses factors that contribute to an environment in social work that fosters attitudes of reluctance toward learning and teaching statistics in research methods…

  1. Statistical Models and Methods for Network Meta-Analysis.

    PubMed

    Madden, L V; Piepho, H-P; Paul, P A

    2016-08-01

    Meta-analysis, the methodology for analyzing the results from multiple independent studies, has grown tremendously in popularity over the last four decades. Although most meta-analyses involve a single effect size (summary result, such as a treatment difference) from each study, there are often multiple treatments of interest across the network of studies in the analysis. Multi-treatment (or network) meta-analysis can be used for simultaneously analyzing the results from all the treatments. However, the methodology is considerably more complicated than for the analysis of a single effect size, and there have not been adequate explanations of the approach for agricultural investigations. We review the methods and models for conducting a network meta-analysis based on frequentist statistical principles, and demonstrate the procedures using a published multi-treatment plant pathology data set. A major advantage of network meta-analysis is that correlations of estimated treatment effects are automatically taken into account when an appropriate model is used. Moreover, treatment comparisons may be possible in a network meta-analysis that are not possible in a single study because all treatments of interest may not be included in any given study. We review several models that consider the study effect as either fixed or random, and show how to interpret model-fitting output. We further show how to model the effect of moderator variables (study-level characteristics) on treatment effects, and present one approach to test for the consistency of treatment effects across the network. Online supplemental files give explanations on fitting the network meta-analytical models using SAS. PMID:27111798

  2. An Introductory Overview of Statistical Methods for Discrete Time Series

    NASA Astrophysics Data System (ADS)

    Meng, X.-L.; California-Harvard AstroStat Collaboration

    2004-08-01

    A number of statistical problems encounted in astrophysics are concerned with discrete time series, such as photon counts with variation in source intensity over time. This talk provides an introductory overview of the current state-of-the-art methods in statistics, including Bayesian methods aided by Markov chain Monte Carlo, for modeling and analyzing such data. These methods have also been successfully applied in other fields, such as economics.

  3. Statistical and Computational Methods for Genetic Diseases: An Overview

    PubMed Central

    Di Taranto, Maria Donata

    2015-01-01

    The identification of causes of genetic diseases has been carried out by several approaches with increasing complexity. Innovation of genetic methodologies leads to the production of large amounts of data that needs the support of statistical and computational methods to be correctly processed. The aim of the paper is to provide an overview of statistical and computational methods paying attention to methods for the sequence analysis and complex diseases. PMID:26106440

  4. Statistical Morphometry of Small Martian Craters: New Methods and Results

    NASA Astrophysics Data System (ADS)

    Watters, W. A.; Geiger, L.; Fendrock, M.; Gibson, R.; Radford, A.

    2015-05-01

    Methods for automatic morphometric characterization of craters for large statistical studies; measured dependence of shape on size, terrain, modification, and velocity (via primary-to-secondary distance); evaluation of Ames Stereo Pipeline DEMs.

  5. Comparison of methods for computing streamflow statistics for Pennsylvania streams

    USGS Publications Warehouse

    Ehlke, Marla H.; Reed, Lloyd A.

    1999-01-01

    Methods for computing streamflow statistics intended for use on ungaged locations on Pennsylvania streams are presented and compared to frequency distributions of gaged streamflow data. The streamflow statistics used in the comparisons include the 7-day 10-year low flow, 50-year flood flow, and the 100-year flood flow; additional statistics are presented. Streamflow statistics for gaged locations on streams in Pennsylvania were computed using three methods for the comparisons: 1) Log-Pearson type III frequency distribution (Log-Pearson) of continuous-record streamflow data, 2) regional regression equations developed by the U.S. Geological Survey in 1982 (WRI 82-21), and 3) regional regression equations developed by the Pennsylvania State University in 1981 (PSU-IV). Log-Pearson distribution was considered the reference method for evaluation of the regional regression equations. Low-flow statistics were computed using the Log-Pearson distribution and WRI 82-21, whereas flood-flow statistics were computed using all three methods. The urban adjustment for PSU-IV was modified from the recommended computation to exclude Philadelphia and the surrounding areas (region 1) from the adjustment. Adjustments for storage area for PSU-IV were also slightly modified. A comparison of the 7-day 10-year low flow computed from Log-Pearson distribution and WRI-82- 21 showed that the methods produced significantly different values for about 7 percent of the state. The same methods produced 50-year and 100-year flood flows that were significantly different for about 24 percent of the state. Flood-flow statistics computed using Log-Pearson distribution and PSU-IV were not significantly different in any regions of the state. These findings are based on a statistical comparison using the t-test on signed ranks and graphical methods.

  6. Statistical limitations in functional neuroimaging. I. Non-inferential methods and statistical models.

    PubMed Central

    Petersson, K M; Nichols, T E; Poline, J B; Holmes, A P

    1999-01-01

    Functional neuroimaging (FNI) provides experimental access to the intact living brain making it possible to study higher cognitive functions in humans. In this review and in a companion paper in this issue, we discuss some common methods used to analyse FNI data. The emphasis in both papers is on assumptions and limitations of the methods reviewed. There are several methods available to analyse FNI data indicating that none is optimal for all purposes. In order to make optimal use of the methods available it is important to know the limits of applicability. For the interpretation of FNI results it is also important to take into account the assumptions, approximations and inherent limitations of the methods used. This paper gives a brief overview over some non-inferential descriptive methods and common statistical models used in FNI. Issues relating to the complex problem of model selection are discussed. In general, proper model selection is a necessary prerequisite for the validity of the subsequent statistical inference. The non-inferential section describes methods that, combined with inspection of parameter estimates and other simple measures, can aid in the process of model selection and verification of assumptions. The section on statistical models covers approaches to global normalization and some aspects of univariate, multivariate, and Bayesian models. Finally, approaches to functional connectivity and effective connectivity are discussed. In the companion paper we review issues related to signal detection and statistical inference. PMID:10466149

  7. Applications of computer-intensive statistical methods to environmental research.

    PubMed

    Pitt, D G; Kreutzweiser, D P

    1998-02-01

    Conventional statistical approaches rely heavily on the properties of the central limit theorem to bridge the gap between the characteristics of a sample and some theoretical sampling distribution. Problems associated with nonrandom sampling, unknown population distributions, heterogeneous variances, small sample sizes, and missing data jeopardize the assumptions of such approaches and cast skepticism on conclusions. Conventional nonparametric alternatives offer freedom from distribution assumptions, but design limitations and loss of power can be serious drawbacks. With the data-processing capacity of today's computers, a new dimension of distribution-free statistical methods has evolved that addresses many of the limitations of conventional parametric and nonparametric methods. Computer-intensive statistical methods involve reshuffling, resampling, or simulating a data set thousands of times to empirically define a sampling distribution for a chosen test statistic. The only assumption necessary for valid results is the random assignment of experimental units to the test groups or treatments. Application to a real data set illustrates the advantages of these methods, including freedom from distribution assumptions without loss of power, complete choice over test statistics, easy adaptation to design complexities and missing data, and considerable intuitive appeal. The illustrations also reveal that computer-intensive methods can be more time consuming than conventional methods and the amount of computer code required to orchestrate reshuffling, resampling, or simulation procedures can be appreciable. PMID:9515080

  8. Scene-based nonuniformity correction method using multiscale constant statistics

    NASA Astrophysics Data System (ADS)

    Zuo, Chao; Chen, Qian; Gu, Guohua; Sui, Xiubao; Qian, Weixian

    2011-08-01

    In scene-based nonuniformity correction (NUC) methods for infrared focal plane array cameras, the statistical approaches have been well studied because of their lower computational complexity. However, when the assumptions imposed by statistical algorithms are violated, their performance is poor. Moreover, many of these techniques, like the global constant statistics method, usually need tens of thousands of image frames to obtain a good NUC result. In this paper, we introduce a new statistical NUC method called the multiscale constant statistics (MSCS). The MSCS statically considers that the spatial scale of the temporal constant distribution expands over time. Under the assumption that the nonuniformity is distributed in a higher spatial frequency domain, the spatial range for gain and offset estimates gradually expands to guarantee fast compensation for nonuniformity. Furthermore, an exponential window and a tolerance interval for the acquired data are introduced to capture the drift in nonuniformity and eliminate the ghosting artifacts. The strength of the proposed method lies in its simplicity, low computational complexity, and its good trade-off between convergence rate and correction precision. The NUC ability of the proposed method is demonstrated by using infrared video sequences with both synthetic and real nonuniformity.

  9. Statistical Methods for Establishing Personalized Treatment Rules in Oncology

    PubMed Central

    Ma, Junsheng; Hobbs, Brian P.; Stingo, Francesco C.

    2015-01-01

    The process for using statistical inference to establish personalized treatment strategies requires specific techniques for data-analysis that optimize the combination of competing therapies with candidate genetic features and characteristics of the patient and disease. A wide variety of methods have been developed. However, heretofore the usefulness of these recent advances has not been fully recognized by the oncology community, and the scope of their applications has not been summarized. In this paper, we provide an overview of statistical methods for establishing optimal treatment rules for personalized medicine and discuss specific examples in various medical contexts with oncology as an emphasis. We also point the reader to statistical software for implementation of the methods when available. PMID:26446492

  10. Statistical method of evaluation of flip-flop dynamical parameters

    NASA Astrophysics Data System (ADS)

    Wieczorek, P. Z.; Opalski, L. J.

    2008-01-01

    This paper presents statistical algorithm and measurement system for precise evaluation of flip-flop dynamical parameters in asynchronous operation. The analyzed flip-flop parameters are failure probability, MTBF and propagation delay. It is shown how these parameters depend on metastable operation of flip-flops. The numerical and hardware solutions shown in article allow for precise and reliable comparison of flip-flops. Also the analysis of influence of flip-flop electrical parameters of flip-flop electrical parameters on their metastable operation is possible with use of presented statistical method. Statistical estimation of parameters of flip-flops in which metastability occurs, seems to be more reliable than standard empirical methods of flip-flop analysis. Presented method allows for showing inaccuracies in theoretical model of metastability.

  11. How adequate are the current methods of lead extraction? A review of the efficiency and safety of transvenous lead extraction methods.

    PubMed

    Buiten, Maurits S; van der Heijden, Aafke C; Schalij, Martin J; van Erven, Lieselot

    2015-05-01

    Currently several extraction tools are available in order to allow safe and successful transvenous lead extraction (TLE) of pacemaker and ICD leads; however, no directives exist to guide physicians in their choice of extraction tools and approaches. To aim of the current review is to provide an overview of the success and complication rates of different extraction methods and tools available. A comprehensive search of all published literature was conducted in the databases of PubMed, Embase, Web of Science, and Central. Included papers were original articles describing a specific method of TLE and the corresponding success rates of at least 50 patients. Fifty-three studies were included; the majority (56%) utilized 2 (1-4) different venous extraction approaches (subclavian and femoral), the median number of extraction tools used was 3 (1-6). A stepwise approach was utilized in the majority of the studies, starting with simple traction which resulted in successful TLE in 7-85% of the leads. When applicable the procedure was continued with non-powered tools resulting in a successful extraction of 34-87% leads. Subsequently, powered tools were applied whereby success rates further increased to 74-100%. The final step in TLE was usually utilized by femoral snare leading to an overall TLE success rate of 96-100%. The median procedure-related mortality and major complication described were, respectively, 0% (0-3%) and 1% (0-7%) per patient. In conclusion, a stepwise extraction approach can result in a clinical successful TLE in up to 100% of the leads with a relatively low risk of procedure-related mortality and complications. PMID:25687745

  12. Knowledge acquisition for expert systems using statistical methods

    NASA Technical Reports Server (NTRS)

    Belkin, Brenda L.; Stengel, Robert F.

    1991-01-01

    A common problem in the design of expert systems is the definition of rules from data obtained in system operation or simulation. A statistical method for generating rule bases from numerical data, motivated by an example based on aircraft navigation with multiple sensors is presented. The specific objective is to design an expert system that selects a satisfactory suite of measurements from a dissimilar, redundant set, given an arbitrary navigation geometry and possible sensor failures. The systematic development of a Navigation Sensor Management (NSM) Expert System from Kalman Filter covariance data is described. The development method invokes two statistical techniques: Analysis-of-Variance (ANOVA) and the ID3 algorithm. The ANOVA technique indicates whether variations of problem parameters give statistically different covariance results, and the ID3 algorithm identifies the relationships between the problem parameters using probabilistic knowledge extracted from a simulation example set.

  13. Statistical methods of parameter estimation for deterministically chaotic time series.

    PubMed

    Pisarenko, V F; Sornette, D

    2004-03-01

    We discuss the possibility of applying some standard statistical methods (the least-square method, the maximum likelihood method, and the method of statistical moments for estimation of parameters) to deterministically chaotic low-dimensional dynamic system (the logistic map) containing an observational noise. A "segmentation fitting" maximum likelihood (ML) method is suggested to estimate the structural parameter of the logistic map along with the initial value x(1) considered as an additional unknown parameter. The segmentation fitting method, called "piece-wise" ML, is similar in spirit but simpler and has smaller bias than the "multiple shooting" previously proposed. Comparisons with different previously proposed techniques on simulated numerical examples give favorable results (at least, for the investigated combinations of sample size N and noise level). Besides, unlike some suggested techniques, our method does not require the a priori knowledge of the noise variance. We also clarify the nature of the inherent difficulties in the statistical analysis of deterministically chaotic time series and the status of previously proposed Bayesian approaches. We note the trade off between the need of using a large number of data points in the ML analysis to decrease the bias (to guarantee consistency of the estimation) and the unstable nature of dynamical trajectories with exponentially fast loss of memory of the initial condition. The method of statistical moments for the estimation of the parameter of the logistic map is discussed. This method seems to be the unique method whose consistency for deterministically chaotic time series is proved so far theoretically (not only numerically). PMID:15089376

  14. Landslide Susceptibility Statistical Methods: A Critical and Systematic Literature Review

    NASA Astrophysics Data System (ADS)

    Mihir, Monika; Malamud, Bruce; Rossi, Mauro; Reichenbach, Paola; Ardizzone, Francesca

    2014-05-01

    Landslide susceptibility assessment, the subject of this systematic review, is aimed at understanding the spatial probability of slope failures under a set of geomorphological and environmental conditions. It is estimated that about 375 landslides that occur globally each year are fatal, with around 4600 people killed per year. Past studies have brought out the increasing cost of landslide damages which primarily can be attributed to human occupation and increased human activities in the vulnerable environments. Many scientists, to evaluate and reduce landslide risk, have made an effort to efficiently map landslide susceptibility using different statistical methods. In this paper, we do a critical and systematic landslide susceptibility literature review, in terms of the different statistical methods used. For each of a broad set of studies reviewed we note: (i) study geography region and areal extent, (ii) landslide types, (iii) inventory type and temporal period covered, (iv) mapping technique (v) thematic variables used (vi) statistical models, (vii) assessment of model skill, (viii) uncertainty assessment methods, (ix) validation methods. We then pulled out broad trends within our review of landslide susceptibility, particularly regarding the statistical methods. We found that the most common statistical methods used in the study of landslide susceptibility include logistic regression, artificial neural network, discriminant analysis and weight of evidence. Although most of the studies we reviewed assessed the model skill, very few assessed model uncertainty. In terms of geographic extent, the largest number of landslide susceptibility zonations were in Turkey, Korea, Spain, Italy and Malaysia. However, there are also many landslides and fatalities in other localities, particularly India, China, Philippines, Nepal and Indonesia, Guatemala, and Pakistan, where there are much fewer landslide susceptibility studies available in the peer-review literature. This

  15. Conventional and Newer Statistical Methods in Meta-Analysis.

    ERIC Educational Resources Information Center

    Kulik, James A.; Kulik, Chen-Lin C.

    The assumptions and consequences of applying conventional and newer statistical methods to meta-analytic data sets are reviewed. The application of the two approaches to a meta-analytic data set described by L. V. Hedges (1984) illustrates the differences. Hedges analyzed six studies of the effects of open education on student cooperation. The…

  16. Peer-Assisted Learning in Research Methods and Statistics

    ERIC Educational Resources Information Center

    Stone, Anna; Meade, Claire; Watling, Rosamond

    2012-01-01

    Feedback from students on a Level 1 Research Methods and Statistics module, studied as a core part of a BSc Psychology programme, highlighted demand for additional tutorials to help them to understand basic concepts. Students in their final year of study commonly request work experience to enhance their employability. All students on the Level 1…

  17. System and method for statistically monitoring and analyzing sensed conditions

    DOEpatents

    Pebay, Philippe P.; Brandt, James M. , Gentile; Ann C. , Marzouk; Youssef M. , Hale; Darrian J. , Thompson; David C.

    2010-07-13

    A system and method of monitoring and analyzing a plurality of attributes for an alarm condition is disclosed. The attributes are processed and/or unprocessed values of sensed conditions of a collection of a statistically significant number of statistically similar components subjected to varying environmental conditions. The attribute values are used to compute the normal behaviors of some of the attributes and also used to infer parameters of a set of models. Relative probabilities of some attribute values are then computed and used along with the set of models to determine whether an alarm condition is met. The alarm conditions are used to prevent or reduce the impact of impending failure.

  18. System and method for statistically monitoring and analyzing sensed conditions

    DOEpatents

    Pebay, Philippe P.; Brandt, James M.; Gentile, Ann C.; Marzouk, Youssef M.; Hale, Darrian J.; Thompson, David C.

    2011-01-25

    A system and method of monitoring and analyzing a plurality of attributes for an alarm condition is disclosed. The attributes are processed and/or unprocessed values of sensed conditions of a collection of a statistically significant number of statistically similar components subjected to varying environmental conditions. The attribute values are used to compute the normal behaviors of some of the attributes and also used to infer parameters of a set of models. Relative probabilities of some attribute values are then computed and used along with the set of models to determine whether an alarm condition is met. The alarm conditions are used to prevent or reduce the impact of impending failure.

  19. System and method for statistically monitoring and analyzing sensed conditions

    DOEpatents

    Pebay, Philippe P.; Brandt, James M.; Gentile, Ann C.; Marzouk, Youssef M.; Hale, Darrian J.; Thompson, David C.

    2011-01-04

    A system and method of monitoring and analyzing a plurality of attributes for an alarm condition is disclosed. The attributes are processed and/or unprocessed values of sensed conditions of a collection of a statistically significant number of statistically similar components subjected to varying environmental conditions. The attribute values are used to compute the normal behaviors of some of the attributes and also used to infer parameters of a set of models. Relative probabilities of some attribute values are then computed and used along with the set of models to determine whether an alarm condition is met. The alarm conditions are used to prevent or reduce the impact of impending failure.

  20. Predicting recreational water quality advisories: A comparison of statistical methods

    USGS Publications Warehouse

    Brooks, Wesley R.; Corsi, Steven R.; Fienen, Michael N.; Carvin, Rebecca B.

    2016-01-01

    Epidemiological studies indicate that fecal indicator bacteria (FIB) in beach water are associated with illnesses among people having contact with the water. In order to mitigate public health impacts, many beaches are posted with an advisory when the concentration of FIB exceeds a beach action value. The most commonly used method of measuring FIB concentration takes 18–24 h before returning a result. In order to avoid the 24 h lag, it has become common to ”nowcast” the FIB concentration using statistical regressions on environmental surrogate variables. Most commonly, nowcast models are estimated using ordinary least squares regression, but other regression methods from the statistical and machine learning literature are sometimes used. This study compares 14 regression methods across 7 Wisconsin beaches to identify which consistently produces the most accurate predictions. A random forest model is identified as the most accurate, followed by multiple regression fit using the adaptive LASSO.

  1. Statistical approaches to pharmacodynamic modeling: motivations, methods, and misperceptions.

    PubMed

    Mick, R; Ratain, M J

    1993-01-01

    We have attempted to outline the fundamental statistical aspects of pharmacodynamic modeling. Unexpected yet substantial variability in effect in a group of similarly treated patients is the key motivation for pharmacodynamic investigations. Pharmacokinetic and/or pharmacodynamic factors may influence this variability. Residual variability in effect that persists after accounting for drug exposure indicates that further statistical modeling with pharmacodynamic factors is warranted. Factors that significantly predict interpatient variability in effect may then be employed to individualize the drug dose. In this paper we have emphasized the need to understand the properties of the effect measure and explanatory variables in terms of scale, distribution, and statistical relationship. The assumptions that underlie many types of statistical models have been discussed. The role of residual analysis has been stressed as a useful method to verify assumptions. We have described transformations and alternative regression methods that are employed when these assumptions are found to be in violation. Sequential selection procedures for the construction of multivariate models have been presented. The importance of assessing model performance has been underscored, most notably in terms of bias and precision. In summary, pharmacodynamic analyses are now commonly performed and reported in the oncologic literature. The content and format of these analyses has been variable. The goals of such analyses are to identify and describe pharmacodynamic relationships and, in many cases, to propose a statistical model. However, the appropriateness and performance of the proposed model are often difficult to judge. Table 1 displays suggestions (in a checklist format) for structuring the presentation of pharmacodynamic analyses, which reflect the topics reviewed in this paper. PMID:8269582

  2. Review of Statistical Methods for Analysing Healthcare Resources and Costs

    PubMed Central

    Mihaylova, Borislava; Briggs, Andrew; O'Hagan, Anthony; Thompson, Simon G

    2011-01-01

    We review statistical methods for analysing healthcare resource use and costs, their ability to address skewness, excess zeros, multimodality and heavy right tails, and their ease for general use. We aim to provide guidance on analysing resource use and costs focusing on randomised trials, although methods often have wider applicability. Twelve broad categories of methods were identified: (I) methods based on the normal distribution, (II) methods following transformation of data, (III) single-distribution generalized linear models (GLMs), (IV) parametric models based on skewed distributions outside the GLM family, (V) models based on mixtures of parametric distributions, (VI) two (or multi)-part and Tobit models, (VII) survival methods, (VIII) non-parametric methods, (IX) methods based on truncation or trimming of data, (X) data components models, (XI) methods based on averaging across models, and (XII) Markov chain methods. Based on this review, our recommendations are that, first, simple methods are preferred in large samples where the near-normality of sample means is assured. Second, in somewhat smaller samples, relatively simple methods, able to deal with one or two of above data characteristics, may be preferable but checking sensitivity to assumptions is necessary. Finally, some more complex methods hold promise, but are relatively untried; their implementation requires substantial expertise and they are not currently recommended for wider applied work. Copyright © 2010 John Wiley & Sons, Ltd. PMID:20799344

  3. Yang-Yang Equilibrium Statistical Mechanics: A Brilliant Method

    NASA Astrophysics Data System (ADS)

    Guan, Xi-Wen; Chen, Yang-Yang

    C. N. Yang and C. P. Yang in 1969 (J. Math. Phys. 10, 1115 (1969)) for the first time proposed a rigorous approach to the thermodynamics of the one-dimensional system of bosons with a delta-function interaction. This paper was a breakthrough in exact statistical mechanics, after C. N. Yang (Phys. Rev. Lett. 19, 1312 (1967)) published his seminal work on the discovery of the Yang-Baxter equation in 1967. Yang and Yang's brilliant method yields significant applications in a wide range of fields of physics. In this communication, we briefly introduce the method of the Yang-Yang equilibrium statistical mechanics and demonstrate a fundamental application of the Yang-Yang method for the study of thermodynamics of the Lieb-Liniger model with strong and weak interactions in a whole temperature regime. We also consider the equivalence between the Yang-Yang's thermodynamic Bethe ansatz equation and the thermodynamics of the ideal gas with the Haldane's generalized exclusion statistics.

  4. Yang-Yang equilibrium statistical mechanics: A brilliant method

    NASA Astrophysics Data System (ADS)

    Guan, Xi-Wen; Chen, Yang-Yang

    2016-03-01

    Yang and Yang in 1969 [J. Math. Phys. 10, 1115 (1969)] for the first time proposed a rigorous approach to the thermodynamics of the one-dimensional system of bosons with a delta-function interaction. This paper was a breakthrough in exact statistical mechanics, after Yang [Phys. Rev. Lett. 19, 1312 (1967)] published his seminal work on the discovery of the Yang-Baxter equation in 1967. Yang and Yang’s brilliant method yields significant applications in a wide range of fields of physics. In this paper, we briefly introduce the method of the Yang-Yang equilibrium statistical mechanics and demonstrate a fundamental application of the Yang-Yang method for the study of thermodynamics of the Lieb-Liniger model with strong and weak interactions in a whole temperature regime. We also consider the equivalence between the Yang-Yang’s thermodynamic Bethe ansatz equation and the thermodynamics of the ideal gas with the Haldane’s generalized exclusion statistics.

  5. Accuracy Evaluation of a Mobile Mapping System with Advanced Statistical Methods

    NASA Astrophysics Data System (ADS)

    Toschi, I.; Rodríguez-Gonzálvez, P.; Remondino, F.; Minto, S.; Orlandini, S.; Fuller, A.

    2015-02-01

    This paper discusses a methodology to evaluate the precision and the accuracy of a commercial Mobile Mapping System (MMS) with advanced statistical methods. So far, the metric potentialities of this emerging mapping technology have been studied in few papers, where generally the assumption that errors follow a normal distribution is made. In fact, this hypothesis should be carefully verified in advance, in order to test how well the Gaussian classic statistics can adapt to datasets that are usually affected by asymmetrical gross errors. The workflow adopted in this study relies on a Gaussian assessment, followed by an outlier filtering process. Finally, non-parametric statistical models are applied, in order to achieve a robust estimation of the error dispersion. Among the different MMSs available on the market, the latest solution provided by RIEGL is here tested, i.e. the VMX-450 Mobile Laser Scanning System. The test-area is the historic city centre of Trento (Italy), selected in order to assess the system performance in dealing with a challenging and historic urban scenario. Reference measures are derived from photogrammetric and Terrestrial Laser Scanning (TLS) surveys. All datasets show a large lack of symmetry that leads to the conclusion that the standard normal parameters are not adequate to assess this type of data. The use of non-normal statistics gives thus a more appropriate description of the data and yields results that meet the quoted a-priori errors.

  6. Statistical Methods Handbook for Advanced Gas Reactor Fuel Materials

    SciTech Connect

    J. J. Einerson

    2005-05-01

    Fuel materials such as kernels, coated particles, and compacts are being manufactured for experiments simulating service in the next generation of high temperature gas reactors. These must meet predefined acceptance specifications. Many tests are performed for quality assurance, and many of these correspond to criteria that must be met with specified confidence, based on random samples. This report describes the statistical methods to be used. The properties of the tests are discussed, including the risk of false acceptance, the risk of false rejection, and the assumption of normality. Methods for calculating sample sizes are also described.

  7. Application of the Bootstrap Statistical Method in Deriving Vibroacoustic Specifications

    NASA Technical Reports Server (NTRS)

    Hughes, William O.; Paez, Thomas L.

    2006-01-01

    This paper discusses the Bootstrap Method for specification of vibroacoustic test specifications. Vibroacoustic test specifications are necessary to properly accept or qualify a spacecraft and its components for the expected acoustic, random vibration and shock environments seen on an expendable launch vehicle. Traditionally, NASA and the U.S. Air Force have employed methods of Normal Tolerance Limits to derive these test levels based upon the amount of data available, and the probability and confidence levels desired. The Normal Tolerance Limit method contains inherent assumptions about the distribution of the data. The Bootstrap is a distribution-free statistical subsampling method which uses the measured data themselves to establish estimates of statistical measures of random sources. This is achieved through the computation of large numbers of Bootstrap replicates of a data measure of interest and the use of these replicates to derive test levels consistent with the probability and confidence desired. The comparison of the results of these two methods is illustrated via an example utilizing actual spacecraft vibroacoustic data.

  8. Statistical methods for handling unwanted variation in metabolomics data

    PubMed Central

    Sysi-Aho, Marko; Jacob, Laurent; Gagnon-Bartsch, Johann A.; Castillo, Sandra; Simpson, Julie A; Speed, Terence P.

    2015-01-01

    Metabolomics experiments are inevitably subject to a component of unwanted variation, due to factors such as batch effects, long runs of samples, and confounding biological variation. Although the removal of this unwanted variation is a vital step in the analysis of metabolomics data, it is considered a gray area in which there is a recognised need to develop a better understanding of the procedures and statistical methods required to achieve statistically relevant optimal biological outcomes. In this paper, we discuss the causes of unwanted variation in metabolomics experiments, review commonly used metabolomics approaches for handling this unwanted variation, and present a statistical approach for the removal of unwanted variation to obtain normalized metabolomics data. The advantages and performance of the approach relative to several widely-used metabolomics normalization approaches are illustrated through two metabolomics studies, and recommendations are provided for choosing and assessing the most suitable normalization method for a given metabolomics experiment. Software for the approach is made freely available online. PMID:25692814

  9. Statistical methods for investigating quiescence and other temporal seismicity patterns

    USGS Publications Warehouse

    Matthews, M.V.; Reasenberg, P.A.

    1988-01-01

    We propose a statistical model and a technique for objective recognition of one of the most commonly cited seismicity patterns:microearthquake quiescence. We use a Poisson process model for seismicity and define a process with quiescence as one with a particular type of piece-wise constant intensity function. From this model, we derive a statistic for testing stationarity against a 'quiescence' alternative. The large-sample null distribution of this statistic is approximated from simulated distributions of appropriate functionals applied to Brownian bridge processes. We point out the restrictiveness of the particular model we propose and of the quiescence idea in general. The fact that there are many point processes which have neither constant nor quiescent rate functions underscores the need to test for and describe nonuniformity thoroughly. We advocate the use of the quiescence test in conjunction with various other tests for nonuniformity and with graphical methods such as density estimation. ideally these methods may promote accurate description of temporal seismicity distributions and useful characterizations of interesting patterns. ?? 1988 Birkha??user Verlag.

  10. FAst STatistics for weak Lensing (FASTLens): fast method for weak lensing statistics and map making

    NASA Astrophysics Data System (ADS)

    Pires, S.; Starck, J.-L.; Amara, A.; Teyssier, R.; Réfrégier, A.; Fadili, J.

    2009-05-01

    With increasingly large data sets, weak lensing measurements are able to measure cosmological parameters with ever-greater precision. However, this increased accuracy also places greater demands on the statistical tools used to extract the available information. To date, the majority of lensing analyses use the two-point statistics of the cosmic shear field. These can be either studied directly using the two-point correlation function or in Fourier space, using the power spectrum. But analysing weak lensing data inevitably involves the masking out of regions, for example to remove bright stars from the field. Masking out the stars is common practice but the gaps in the data need proper handling. In this paper, we show how an inpainting technique allows us to properly fill in these gaps with only NlogN operations, leading to a new image from which we can compute straightforwardly and with a very good accuracy both the power spectrum and the bispectrum. We then propose a new method to compute the bispectrum with a polar FFT algorithm, which has the main advantage of avoiding any interpolation in the Fourier domain. Finally, we propose a new method for dark matter mass map reconstruction from shear observations, which integrates this new inpainting concept. A range of examples based on 3D N-body simulations illustrates the results.

  11. Evidence of Statistical Inconsistency of Phylogenetic Methods in the Presence of Multiple Sequence Alignment Uncertainty

    PubMed Central

    Md Mukarram Hossain, A.S.; Blackburne, Benjamin P.; Shah, Abhijeet; Whelan, Simon

    2015-01-01

    Evolutionary studies usually use a two-step process to investigate sequence data. Step one estimates a multiple sequence alignment (MSA) and step two applies phylogenetic methods to ask evolutionary questions of that MSA. Modern phylogenetic methods infer evolutionary parameters using maximum likelihood or Bayesian inference, mediated by a probabilistic substitution model that describes sequence change over a tree. The statistical properties of these methods mean that more data directly translates to an increased confidence in downstream results, providing the substitution model is adequate and the MSA is correct. Many studies have investigated the robustness of phylogenetic methods in the presence of substitution model misspecification, but few have examined the statistical properties of those methods when the MSA is unknown. This simulation study examines the statistical properties of the complete two-step process when inferring sequence divergence and the phylogenetic tree topology. Both nucleotide and amino acid analyses are negatively affected by the alignment step, both through inaccurate guide tree estimates and through overfitting to that guide tree. For many alignment tools these effects become more pronounced when additional sequences are added to the analysis. Nucleotide sequences are particularly susceptible, with MSA errors leading to statistical support for long-branch attraction artifacts, which are usually associated with gross substitution model misspecification. Amino acid MSAs are more robust, but do tend to arbitrarily resolve multifurcations in favor of the guide tree. No inference strategies produce consistently accurate estimates of divergence between sequences, although amino acid MSAs are again more accurate than their nucleotide counterparts. We conclude with some practical suggestions about how to limit the effect of MSA uncertainty on evolutionary inference. PMID:26139831

  12. Radiological decontamination, survey, and statistical release method for vehicles

    SciTech Connect

    Goodwill, M.E.; Lively, J.W.; Morris, R.L.

    1996-06-01

    Earth-moving vehicles (e.g., dump trucks, belly dumps) commonly haul radiologically contaminated materials from a site being remediated to a disposal site. Traditionally, each vehicle must be surveyed before being released. The logistical difficulties of implementing the traditional approach on a large scale demand that an alternative be devised. A statistical method for assessing product quality from a continuous process was adapted to the vehicle decontamination process. This method produced a sampling scheme that automatically compensates and accommodates fluctuating batch sizes and changing conditions without the need to modify or rectify the sampling scheme in the field. Vehicles are randomly selected (sampled) upon completion of the decontamination process to be surveyed for residual radioactive surface contamination. The frequency of sampling is based on the expected number of vehicles passing through the decontamination process in a given period and the confidence level desired. This process has been successfully used for 1 year at the former uranium millsite in Monticello, Utah (a cleanup site regulated under the Comprehensive Environmental Response, Compensation, and Liability Act). The method forces improvement in the quality of the decontamination process and results in a lower likelihood that vehicles exceeding the surface contamination standards are offered for survey. Implementation of this statistical sampling method on Monticello projects has resulted in more efficient processing of vehicles through decontamination and radiological release, saved hundreds of hours of processing time, provided a high level of confidence that release limits are met, and improved the radiological cleanliness of vehicles leaving the controlled site.

  13. Statistical length measurement method by direct imaging of carbon nanotubes.

    PubMed

    Bengio, E Amram; Tsentalovich, Dmitri E; Behabtu, Natnael; Kleinerman, Olga; Kesselman, Ellina; Schmidt, Judith; Talmon, Yeshayahu; Pasquali, Matteo

    2014-05-14

    The influence of carbon nanotube (CNT) length on their macroscopic properties requires an accurate methodology for CNT length measurement. So far, existing techniques are limited to short (less than a few micrometers) CNTs and sample preparation methods that bias the measured values. Here, we show that the average length of carbon nanotubes (CNTs) can be measured by cryogenic transmission electron microscopy (cryo-TEM) of CNTs in chlorosulfonic acid. The method consists of dissolving at low concentration CNTs in chlorosulfonic acid (a true solvent), imaging the individual CNTs by cryo-TEM, and processing and analyzing the images to determine CNT length. By measuring the total CNT contour length and number of CNT ends in each image, and by applying statistical analysis, we extend the method to cases where each CNT is long enough to span many cryo-TEM images, making the direct length measurement of an entire CNT impractical. Hence, this new technique can be used effectively to estimate samples in a wide range of CNT lengths, although we find that cryo-TEM imaging may bias the measurement towards longer CNTs, which are easier to detect. Our statistical method is also applied to AFM images of CNTs to show that, by using only a few AFM images, it yields estimates that are consistent with literature techniques, based on individually measuring a higher number of CNTs. PMID:24773046

  14. Texture analysis with statistical methods for wheat ear extraction

    NASA Astrophysics Data System (ADS)

    Bakhouche, M.; Cointault, F.; Gouton, P.

    2007-01-01

    In agronomic domain, the simplification of crop counting, necessary for yield prediction and agronomic studies, is an important project for technical institutes such as Arvalis. Although the main objective of our global project is to conceive a mobile robot for natural image acquisition directly in a field, Arvalis has proposed us first to detect by image processing the number of wheat ears in images before to count them, which will allow to obtain the first component of the yield. In this paper we compare different texture image segmentation techniques based on feature extraction by first and higher order statistical methods which have been applied on our images. The extracted features are used for unsupervised pixel classification to obtain the different classes in the image. So, the K-means algorithm is implemented before the choice of a threshold to highlight the ears. Three methods have been tested in this feasibility study with very average error of 6%. Although the evaluation of the quality of the detection is visually done, automatic evaluation algorithms are currently implementing. Moreover, other statistical methods of higher order will be implemented in the future jointly with methods based on spatio-frequential transforms and specific filtering.

  15. Decision Making Method Based on Paraconsistent Annotated Logic and Statistical Method: a Comparison

    NASA Astrophysics Data System (ADS)

    de Carvalho, Fábio Romeu; Brunstein, Israel; Abe, Jair Minoro

    2008-10-01

    Presently, there are new kinds of logic capable of handling uncertain and contradictory data without becoming trivial. Decision making theories based on these logics have shown to be powerful in many aspects regarding more traditional methods based on Statistics. In this paper we intend to outline a first study for a decision making theory based on Paraconsistent Annotated Evidential Logic Eτ (Paraconsistent Decision Method (PDM)) and classical Statistical Decision Method (SDM). Some discussion is presented below.

  16. Statistics

    Cancer.gov

    Links to sources of cancer-related statistics, including the Surveillance, Epidemiology and End Results (SEER) Program, SEER-Medicare datasets, cancer survivor prevalence data, and the Cancer Trends Progress Report.

  17. A whirlwind tour of statistical methods in structural dynamics.

    SciTech Connect

    Booker, J. M.

    2004-01-01

    Several statistical methods and their corresponding principles of application to structural dynamics problems will be presented. This set was chosen based upon the projects and their corresponding challenges in the Engineering Sciences & Applications (ESA) Division at Los Alamos National Laboratory and focuses on variance-based uncertainty quantification. Our structural dynamics applications are heavily involved in modeling and simulation, often with sparse data availability. In addition to models, heavy reliance is placed upon the use of expertise and experience. Beginning with principles of inference and prediction, some statistical tools for verification and validation are introduced. Among these are the principles of good experimental design for test and model computation planning, and the combination of data, models and knowledge through the use of Bayes Theorem. A brief introduction to multivariate methods and exploratory data analysis will be presented as part of understanding relationships and variation among important parameters, physical quantities of interest, measurements, inputs and outputs. Finally, the use of these methods and principles will be discussed in drawing conclusions from the validation assessment process under uncertainty.

  18. How to eradicate fraudulent statistical methods: statisticians must do science

    SciTech Connect

    Bross, I.D. )

    1990-12-01

    The two steps necessary for the clinical expression of a mutagenic disease, genetic damage and viability, are countervailing forces and therefore the dosage response curve for mutagens must have a maximum. To illustrate that science is common sense reduced to calculation, a new mathematical derivation of this result and supporting data are given. This example also shows that the term 'context-free' is a snare and a delusion. When statistical methods are used in a scientific context where their assumptions are known to fail and where there is a reasonable presumption of intent to deceive, they are fraudulent. Estimation of low-level mutagenic risks by linear extrapolation from high-dose data is one example of such a method that is widely used by Executive Branch agencies. Other examples are given of fraudulent statistical methods that are currently used in biomedical research done by or for U.S. government agencies. In the long run, it is argued, the surest way to eradicate such fraud is for biostatisticians to do their own science.

  19. Hybrid perturbation methods based on statistical time series models

    NASA Astrophysics Data System (ADS)

    San-Juan, Juan Félix; San-Martín, Montserrat; Pérez, Iván; López, Rosario

    2016-04-01

    In this work we present a new methodology for orbit propagation, the hybrid perturbation theory, based on the combination of an integration method and a prediction technique. The former, which can be a numerical, analytical or semianalytical theory, generates an initial approximation that contains some inaccuracies derived from the fact that, in order to simplify the expressions and subsequent computations, not all the involved forces are taken into account and only low-order terms are considered, not to mention the fact that mathematical models of perturbations not always reproduce physical phenomena with absolute precision. The prediction technique, which can be based on either statistical time series models or computational intelligence methods, is aimed at modelling and reproducing missing dynamics in the previously integrated approximation. This combination results in the precision improvement of conventional numerical, analytical and semianalytical theories for determining the position and velocity of any artificial satellite or space debris object. In order to validate this methodology, we present a family of three hybrid orbit propagators formed by the combination of three different orders of approximation of an analytical theory and a statistical time series model, and analyse their capability to process the effect produced by the flattening of the Earth. The three considered analytical components are the integration of the Kepler problem, a first-order and a second-order analytical theories, whereas the prediction technique is the same in the three cases, namely an additive Holt-Winters method.

  20. SHUFFLE: A New Statistical Bootstrap Method: Applied to Cosmological Filaments

    NASA Astrophysics Data System (ADS)

    Bhavsar, Suketu P.; Bharadwaj, Somnath; Sheth, Jatush V.

    2003-05-01

    We introduce Shuffle, a powerful statistical procedure devised by Bhavsar and Ling [1] to determine the true physical extent of the filaments in the Las Campanas Redshift Survey [LCRS]. At its heart, Shuffle falls in the category of bootstrap like methods [2]. We find that the longest physical filamentary structures in 5 of the 6 LCRS slices are longer than 50 h-1 Mpc but not quite extending to 70 h-1 Mpc. The -3 degree slice contains filamentary structure longer than 70 h-1 Mpc.

  1. Of pacemakers and statistics: the actuarial method extended.

    PubMed

    Dussel, J; Wolbarst, A B; Scott-Millar, R N; Obel, I W

    1980-01-01

    Pacemakers cease functioning because of either natural battery exhaustion (nbe) or component failure (cf). A study of four series of pacemakers shows that a simple extension of the actuarial method, so as to incorporate Normal statistics, makes possible a quantitative differentiation between the two modes of failure. This involves the separation of the overall failure probability density function PDF(t) into constituent parts pdfnbe(t) and pdfcf(t). The approach should allow a meaningful comparison of the characteristics of different pacemaker types. PMID:6160497

  2. Statistical estimation of mineral age by K-Ar method

    SciTech Connect

    Vistelius, A.B.; Drubetzkoy, E.R.; Faas, A.V. )

    1989-11-01

    Statistical estimation of age of {sup 40}Ar/{sup 40}K ratios may be considered a result of convolution of uniform and normal distributions with different weights for different minerals. Data from Gul'shad Massif (Nearbalkhash, Kazakhstan, USSR) indicate that {sup 40}Ar/{sup 40}K ratios reflecting the intensity of geochemical processes can be resolved using convolutions. Loss of {sup 40}Ar in biotites is shown whereas hornblende retained the original content of {sup 40}Ar throughout the geological history of the massif. Results demonstrate that different estimation methods must be used for different minerals and different rocks when radiometric ages are employed for dating.

  3. Estimated Accuracy of Three Common Trajectory Statistical Methods

    NASA Technical Reports Server (NTRS)

    Kabashnikov, Vitaliy P.; Chaikovsky, Anatoli P.; Kucsera, Tom L.; Metelskaya, Natalia S.

    2011-01-01

    Three well-known trajectory statistical methods (TSMs), namely concentration field (CF), concentration weighted trajectory (CWT), and potential source contribution function (PSCF) methods were tested using known sources and artificially generated data sets to determine the ability of TSMs to reproduce spatial distribution of the sources. In the works by other authors, the accuracy of the trajectory statistical methods was estimated for particular species and at specified receptor locations. We have obtained a more general statistical estimation of the accuracy of source reconstruction and have found optimum conditions to reconstruct source distributions of atmospheric trace substances. Only virtual pollutants of the primary type were considered. In real world experiments, TSMs are intended for application to a priori unknown sources. Therefore, the accuracy of TSMs has to be tested with all possible spatial distributions of sources. An ensemble of geographical distributions of virtual sources was generated. Spearman s rank order correlation coefficient between spatial distributions of the known virtual and the reconstructed sources was taken to be a quantitative measure of the accuracy. Statistical estimates of the mean correlation coefficient and a range of the most probable values of correlation coefficients were obtained. All the TSMs that were considered here showed similar close results. The maximum of the ratio of the mean correlation to the width of the correlation interval containing the most probable correlation values determines the optimum conditions for reconstruction. An optimal geographical domain roughly coincides with the area supplying most of the substance to the receptor. The optimal domain s size is dependent on the substance decay time. Under optimum reconstruction conditions, the mean correlation coefficients can reach 0.70 0.75. The boundaries of the interval with the most probable correlation values are 0.6 0.9 for the decay time of 240 h

  4. Statistical Methods for Linking Health, Exposure, and Hazards

    PubMed Central

    Mather, Frances Jean; White, LuAnn Ellis; Langlois, Elizabeth Cullen; Shorter, Charles Franklin; Swalm, Christopher Martin; Shaffer, Jeffrey George; Hartley, William Ralph

    2004-01-01

    The Environmental Public Health Tracking Network (EPHTN) proposes to link environmental hazards and exposures to health outcomes. Statistical methods used in case–control and cohort studies to link health outcomes to individual exposure estimates are well developed. However, reliable exposure estimates for many contaminants are not available at the individual level. In these cases, exposure/hazard data are often aggregated over a geographic area, and ecologic models are used to relate health outcome and exposure/hazard. Ecologic models are not without limitations in interpretation. EPHTN data are characteristic of much information currently being collected—they are multivariate, with many predictors and response variables, often aggregated over geographic regions (small and large) and correlated in space and/or time. The methods to model trends in space and time, handle correlation structures in the data, estimate effects, test hypotheses, and predict future outcomes are relatively new and without extensive application in environmental public health. In this article we outline a tiered approach to data analysis for EPHTN and review the use of standard methods for relating exposure/hazards, disease mapping and clustering techniques, Bayesian approaches, Markov chain Monte Carlo methods for estimation of posterior parameters, and geostatistical methods. The advantages and limitations of these methods are discussed. PMID:15471740

  5. A Statistical Process Control Method for Semiconductor Manufacturing

    NASA Astrophysics Data System (ADS)

    Kubo, Tomoaki; Ino, Tomomi; Minami, Kazuhiro; Minami, Masateru; Homma, Tetsuya

    To maintain stable operation of semiconductor fabrication lines, statistical process control (SPC) methods are recognized to be effective. However, in semiconductor fabrication lines, there exist a huge number of process state signals to be monitored, and these signals contain both normally and non-normally distributed data. Therefore, if we try to apply SPC methods to those signals, we need one which satisfies three requirements: 1) It can deal with both normally distributed data, and non-normally distributed data, 2) It can be set up automatically, 3) It can be easily understood by engineers and technicians. In this paper, we propose a new SPC method which satisfies these three requirements at the same time. This method uses similar rules to the Shewhart chart, but can deal with non-normally distributed data by introducing “effective standard deviations”. Usefulness of this method is demonstrated by comparing false alarm ratios to that of the Shewhart chart method. In the demonstration, we use various kinds of artificially generated data, and real data observed in a chemical vapor deposition (CVD) process tool in a semiconductor fabrication line.

  6. FOREWORD: Special issue on Statistical and Probabilistic Methods for Metrology

    NASA Astrophysics Data System (ADS)

    Bich, Walter; Cox, Maurice G.

    2006-08-01

    This special issue of Metrologia is the first that is not devoted to units, or constants, or measurement techniques in some specific field of metrology, but to the generic topic of statistical and probabilistic methods for metrology. The number of papers on this subject in measurement journals, and in Metrologia in particular, has continued to increase over the years, driven by the publication of the Guide to the Expression of Uncertainty in Measurement (GUM) [1] and the Mutual Recognition Arrangement (MRA) of the CIPM [2]. The former stimulated metrologists to think in greater depth about the appropriate modelling of their measurements, in order to provide uncertainty evaluations associated with measurement results. The latter obliged the metrological community to investigate reliable measures for assessing the calibration and measurement capabilities declared by the national metrology institutes (NMIs). Furthermore, statistical analysis of measurement data became even more important than hitherto, with the need, on the one hand, to treat the greater quantities of data provided by sophisticated measurement systems, and, on the other, to deal appropriately with relatively small sets of data that are difficult or expensive to obtain. The importance of supporting the GUM and extending its provisions was recognized by the formation in the year 2000 of Working Group 1, Measurement uncertainty, of the Joint Committee for Guides in Metrology. The need to provide guidance on key comparison data evaluation was recognized by the formation in the year 2001 of the BIPM Director's Advisory Group on Uncertainty. A further international initiative was the revision, in the year 2004, of the remit and title of a working group of ISO/TC 69, Application of Statistical Methods, to reflect the need to concentrate more on statistical methods to support measurement uncertainty evaluation. These international activities are supplemented by national programmes such as the Software Support

  7. New statistical method for machine-printed Arabic character recognition

    NASA Astrophysics Data System (ADS)

    Wang, Hua; Ding, Xiaoqing; Jin, Jianming; Halmurat, M.

    2004-12-01

    Although about 300 million people worldwide, in several different languages, take Arabic characters for writing, Arabic OCR has not been researched as thoroughly as other widely used characters (Latin or Chinese). In this paper, a new statistical method is developed to recognize machine-printed Arabic characters. Firstly, the entire Arabic character set is pre-classified into 32 sub-sets in terms of character forms, special zones that characters occupy and component information. Then directional features are extracted based on which modified quadratic discriminant function (MQDF) is utilized as classifier to deal with classification task. Finally, similar characters are discriminated before outputting recognition results. Encouraging experimental results on test sets show the validity of proposed method.

  8. New statistical method for machine-printed Arabic character recognition

    NASA Astrophysics Data System (ADS)

    Wang, Hua; Ding, Xiaoqing; Jin, Jianming; Halmurat, M.

    2005-01-01

    Although about 300 million people worldwide, in several different languages, take Arabic characters for writing, Arabic OCR has not been researched as thoroughly as other widely used characters (Latin or Chinese). In this paper, a new statistical method is developed to recognize machine-printed Arabic characters. Firstly, the entire Arabic character set is pre-classified into 32 sub-sets in terms of character forms, special zones that characters occupy and component information. Then directional features are extracted based on which modified quadratic discriminant function (MQDF) is utilized as classifier to deal with classification task. Finally, similar characters are discriminated before outputting recognition results. Encouraging experimental results on test sets show the validity of proposed method.

  9. Regional homogenization of surface temperature records using robust statistical methods

    NASA Astrophysics Data System (ADS)

    Pintar, A. L.; Possolo, A.; Zhang, N. F.

    2013-09-01

    An algorithm is described that is intended to estimate and remove spurious influences from the surface temperature record at a meteorological station, which may be due to changes in the location of the station or in its environment, or in the method used to make measurements, and which are unrelated to climate change, similarly to [1]. The estimate of these influences is based on a comparison of non-parametric decompositions of the target series with series measured at other stations in a neighborhood of the target series. The uncertainty of the estimated spurious artifacts is determined using a statistical bootstrap method that accounts for temporal correlation structure beyond what is expected from seasonal effects. Our computer-intensive bootstrap procedure lends itself readily to parallelization, which makes the algorithm practicable for large collections of stations. The role that the proposed procedure may play in practice is contingent on the results of large-scale testing, still under way, using historical data.

  10. Statistical methods for the blood beryllium lymphocyte proliferation test

    SciTech Connect

    Frome, E.L.; Smith, M.H.; Littlefield, L.G.

    1996-10-01

    The blood beryllium lymphocyte proliferation test (BeLPT) is a modification of the standard lymphocyte proliferation test that is used to identify persons who may have chronic beryllium disease. A major problem in the interpretation of BeLPT test results is outlying data values among the replicate well counts ({approx}7%). A log-linear regression model is used to describe the expected well counts for each set of Be exposure conditions, and the variance of the well counts is proportional to the square of the expected count. Two outlier-resistant regression methods are used to estimate stimulation indices (SIs) and the coefficient of variation. The first approach uses least absolute values (LAV) on the log of the well counts as a method for estimation; the second approach uses a resistant regression version of maximum quasi-likelihood estimation. A major advantage of these resistant methods is that they make it unnecessary to identify and delete outliers. These two new methods for the statistical analysis of the BeLPT data and the current outlier rejection method are applied to 173 BeLPT assays. We strongly recommend the LAV method for routine analysis of the BeLPT. Outliers are important when trying to identify individuals with beryllium hypersensitivity, since these individuals typically have large positive SI values. A new method for identifying large SIs using combined data from the nonexposed group and the beryllium workers is proposed. The log(SI)s are described with a Gaussian distribution with location and scale parameters estimated using resistant methods. This approach is applied to the test data and results are compared with those obtained from the current method. 24 refs., 9 figs., 8 tabs.

  11. Statistical method for detecting structural change in the growth process.

    PubMed

    Ninomiya, Yoshiyuki; Yoshimoto, Atsushi

    2008-03-01

    Due to competition among individual trees and other exogenous factors that change the growth environment, each tree grows following its own growth trend with some structural changes in growth over time. In the present article, a new method is proposed to detect a structural change in the growth process. We formulate the method as a simple statistical test for signal detection without constructing any specific model for the structural change. To evaluate the p-value of the test, the tube method is developed because the regular distribution theory is insufficient. Using two sets of tree diameter growth data sampled from planted forest stands of Cryptomeria japonica in Japan, we conduct an analysis of identifying the effect of thinning on the growth process as a structural change. Our results demonstrate that the proposed method is useful to identify the structural change caused by thinning. We also provide the properties of the method in terms of the size and power of the test. PMID:17608782

  12. Measurement of Plethysmogram and Statistical Method for Analysis

    NASA Astrophysics Data System (ADS)

    Shimizu, Toshihiro

    The plethysmogram is measured at different points of human body by using the photo interrupter, which sensitively depends on the physical and mental situation of human body. In this paper the statistical method of the data-analysis is investigated to discuss the dependence of plethysmogram on stress and aging. The first one is the representation method based on the return map, which provides usuful information for the waveform, the flucuation in phase and the fluctuation in amplitude. The return map method makes it possible to understand the fluctuation of plethymogram in amplitude and in phase more clearly and globally than in the conventional power spectrum method. The second is the Lisajous plot and the correlation function to analyze the phase difference between the plethysmograms of the right finger tip and of the left finger tip. The third is the R-index, from which we can estimate “the age of the blood flow”. The R-index is defined by the global character of plethysmogram, which is different from the usual APG-index. The stress- and age-dependence of plethysmogram is discussed by using these methods.

  13. New Statistical Learning Methods for Estimating Optimal Dynamic Treatment Regimes

    PubMed Central

    Zhao, Ying-Qi; Zeng, Donglin; Laber, Eric B.; Kosorok, Michael R.

    2014-01-01

    Dynamic treatment regimes (DTRs) are sequential decision rules for individual patients that can adapt over time to an evolving illness. The goal is to accommodate heterogeneity among patients and find the DTR which will produce the best long term outcome if implemented. We introduce two new statistical learning methods for estimating the optimal DTR, termed backward outcome weighted learning (BOWL), and simultaneous outcome weighted learning (SOWL). These approaches convert individualized treatment selection into an either sequential or simultaneous classification problem, and can thus be applied by modifying existing machine learning techniques. The proposed methods are based on directly maximizing over all DTRs a nonparametric estimator of the expected long-term outcome; this is fundamentally different than regression-based methods, for example Q-learning, which indirectly attempt such maximization and rely heavily on the correctness of postulated regression models. We prove that the resulting rules are consistent, and provide finite sample bounds for the errors using the estimated rules. Simulation results suggest the proposed methods produce superior DTRs compared with Q-learning especially in small samples. We illustrate the methods using data from a clinical trial for smoking cessation. PMID:26236062

  14. Jet Noise Diagnostics Supporting Statistical Noise Prediction Methods

    NASA Technical Reports Server (NTRS)

    Bridges, James E.

    2006-01-01

    compared against measurements of mean and rms velocity statistics over a range of jet speeds and temperatures. Models for flow parameters used in the acoustic analogy, most notably the space-time correlations of velocity, have been compared against direct measurements, and modified to better fit the observed data. These measurements have been extremely challenging for hot, high speed jets, and represent a sizeable investment in instrumentation development. As an intermediate check that the analysis is predicting the physics intended, phased arrays have been employed to measure source distributions for a wide range of jet cases. And finally, careful far-field spectral directivity measurements have been taken for final validation of the prediction code. Examples of each of these experimental efforts will be presented. The main result of these efforts is a noise prediction code, named JeNo, which is in middevelopment. JeNo is able to consistently predict spectral directivity, including aft angle directivity, for subsonic cold jets of most geometries. Current development on JeNo is focused on extending its capability to hot jets, requiring inclusion of a previously neglected second source associated with thermal fluctuations. A secondary result of the intensive experimentation is the archiving of various flow statistics applicable to other acoustic analogies and to development of time-resolved prediction methods. These will be of lasting value as we look ahead at future challenges to the aeroacoustic experimentalist.

  15. Development and testing of improved statistical wind power forecasting methods.

    SciTech Connect

    Mendes, J.; Bessa, R.J.; Keko, H.; Sumaili, J.; Miranda, V.; Ferreira, C.; Gama, J.; Botterud, A.; Zhou, Z.; Wang, J.

    2011-12-06

    (with spatial and/or temporal dependence). Statistical approaches to uncertainty forecasting basically consist of estimating the uncertainty based on observed forecasting errors. Quantile regression (QR) is currently a commonly used approach in uncertainty forecasting. In Chapter 3, we propose new statistical approaches to the uncertainty estimation problem by employing kernel density forecast (KDF) methods. We use two estimators in both offline and time-adaptive modes, namely, the Nadaraya-Watson (NW) and Quantilecopula (QC) estimators. We conduct detailed tests of the new approaches using QR as a benchmark. One of the major issues in wind power generation are sudden and large changes of wind power output over a short period of time, namely ramping events. In Chapter 4, we perform a comparative study of existing definitions and methodologies for ramp forecasting. We also introduce a new probabilistic method for ramp event detection. The method starts with a stochastic algorithm that generates wind power scenarios, which are passed through a high-pass filter for ramp detection and estimation of the likelihood of ramp events to happen. The report is organized as follows: Chapter 2 presents the results of the application of ITL training criteria to deterministic WPF; Chapter 3 reports the study on probabilistic WPF, including new contributions to wind power uncertainty forecasting; Chapter 4 presents a new method to predict and visualize ramp events, comparing it with state-of-the-art methodologies; Chapter 5 briefly summarizes the main findings and contributions of this report.

  16. Data and statistical methods for analysis of trends and patterns

    SciTech Connect

    Atwood, C.L.; Gentillon, C.D.; Wilson, G.E.

    1992-11-01

    This report summarizes topics considered at a working meeting on data and statistical methods for analysis of trends and patterns in US commercial nuclear power plants. This meeting was sponsored by the Office of Analysis and Evaluation of Operational Data (AEOD) of the Nuclear Regulatory Commission (NRC). Three data sets are briefly described: Nuclear Plant Reliability Data System (NPRDS), Licensee Event Report (LER) data, and Performance Indicator data. Two types of study are emphasized: screening studies, to see if any trends or patterns appear to be present; and detailed studies, which are more concerned with checking the analysis assumptions, modeling any patterns that are present, and searching for causes. A prescription is given for a screening study, and ideas are suggested for a detailed study, when the data take of any of three forms: counts of events per time, counts of events per demand, and non-event data.

  17. Using the statistical analysis method to assess the landslide susceptibility

    NASA Astrophysics Data System (ADS)

    Chan, Hsun-Chuan; Chen, Bo-An; Wen, Yo-Ting

    2015-04-01

    This study assessed the landslide susceptibility in Jing-Shan River upstream watershed, central Taiwan. The landslide inventories during typhoons Toraji in 2001, Mindulle in 2004, Kalmaegi and Sinlaku in 2008, Morakot in 2009, and the 0719 rainfall event in 2011, which were established by Taiwan Central Geological Survey, were used as landslide data. This study aims to assess the landslide susceptibility by using different statistical methods including logistic regression, instability index method and support vector machine (SVM). After the evaluations, the elevation, slope, slope aspect, lithology, terrain roughness, slope roughness, plan curvature, profile curvature, total curvature, average of rainfall were chosen as the landslide factors. The validity of the three established models was further examined by the receiver operating characteristic curve. The result of logistic regression showed that the factor of terrain roughness and slope roughness had a stronger impact on the susceptibility value. Instability index method showed that the factor of terrain roughness and lithology had a stronger impact on the susceptibility value. Due to the fact that the use of instability index method may lead to possible underestimation around the river side. In addition, landslide susceptibility indicated that the use of instability index method laid a potential issue about the number of factor classification. An increase of the number of factor classification may cause excessive variation coefficient of the factor. An decrease of the number of factor classification may make a large range of nearby cells classified into the same susceptibility level. Finally, using the receiver operating characteristic curve discriminate the three models. SVM is a preferred method than the others in assessment of landslide susceptibility. Moreover, SVM is further suggested to be nearly logistic regression in terms of recognizing the medium-high and high susceptibility.

  18. A Comparison of Three Presentation Methods of Teaching Statistics.

    ERIC Educational Resources Information Center

    Packard, Abbot L.; And Others

    The use of computer assisted instruction in teaching statistical concepts was studied. Students enrolled in classes in education who lacked statistical experience participated. Knowledge questions for pretest and posttest assessments were prepared from a pool of questions used in the statistics department of the College of Education at Virginia…

  19. Systematic variational method for statistical nonlinear state and parameter estimation

    NASA Astrophysics Data System (ADS)

    Ye, Jingxin; Rey, Daniel; Kadakia, Nirag; Eldridge, Michael; Morone, Uriel I.; Rozdeba, Paul; Abarbanel, Henry D. I.; Quinn, John C.

    2015-11-01

    In statistical data assimilation one evaluates the conditional expected values, conditioned on measurements, of interesting quantities on the path of a model through observation and prediction windows. This often requires working with very high dimensional integrals in the discrete time descriptions of the observations and model dynamics, which become functional integrals in the continuous-time limit. Two familiar methods for performing these integrals include (1) Monte Carlo calculations and (2) variational approximations using the method of Laplace plus perturbative corrections to the dominant contributions. We attend here to aspects of the Laplace approximation and develop an annealing method for locating the variational path satisfying the Euler-Lagrange equations that comprises the major contribution to the integrals. This begins with the identification of the minimum action path starting with a situation where the model dynamics is totally unresolved in state space, and the consistent minimum of the variational problem is known. We then proceed to slowly increase the model resolution, seeking to remain in the basin of the minimum action path, until a path that gives the dominant contribution to the integral is identified. After a discussion of some general issues, we give examples of the assimilation process for some simple, instructive models from the geophysical literature. Then we explore a slightly richer model of the same type with two distinct time scales. This is followed by a model characterizing the biophysics of individual neurons.

  20. Statistically qualified neuro-analytic failure detection method and system

    DOEpatents

    Vilim, Richard B.; Garcia, Humberto E.; Chen, Frederick W.

    2002-03-02

    An apparatus and method for monitoring a process involve development and application of a statistically qualified neuro-analytic (SQNA) model to accurately and reliably identify process change. The development of the SQNA model is accomplished in two stages: deterministic model adaption and stochastic model modification of the deterministic model adaptation. Deterministic model adaption involves formulating an analytic model of the process representing known process characteristics, augmenting the analytic model with a neural network that captures unknown process characteristics, and training the resulting neuro-analytic model by adjusting the neural network weights according to a unique scaled equation error minimization technique. Stochastic model modification involves qualifying any remaining uncertainty in the trained neuro-analytic model by formulating a likelihood function, given an error propagation equation, for computing the probability that the neuro-analytic model generates measured process output. Preferably, the developed SQNA model is validated using known sequential probability ratio tests and applied to the process as an on-line monitoring system. Illustrative of the method and apparatus, the method is applied to a peristaltic pump system.

  1. Systematic variational method for statistical nonlinear state and parameter estimation.

    PubMed

    Ye, Jingxin; Rey, Daniel; Kadakia, Nirag; Eldridge, Michael; Morone, Uriel I; Rozdeba, Paul; Abarbanel, Henry D I; Quinn, John C

    2015-11-01

    In statistical data assimilation one evaluates the conditional expected values, conditioned on measurements, of interesting quantities on the path of a model through observation and prediction windows. This often requires working with very high dimensional integrals in the discrete time descriptions of the observations and model dynamics, which become functional integrals in the continuous-time limit. Two familiar methods for performing these integrals include (1) Monte Carlo calculations and (2) variational approximations using the method of Laplace plus perturbative corrections to the dominant contributions. We attend here to aspects of the Laplace approximation and develop an annealing method for locating the variational path satisfying the Euler-Lagrange equations that comprises the major contribution to the integrals. This begins with the identification of the minimum action path starting with a situation where the model dynamics is totally unresolved in state space, and the consistent minimum of the variational problem is known. We then proceed to slowly increase the model resolution, seeking to remain in the basin of the minimum action path, until a path that gives the dominant contribution to the integral is identified. After a discussion of some general issues, we give examples of the assimilation process for some simple, instructive models from the geophysical literature. Then we explore a slightly richer model of the same type with two distinct time scales. This is followed by a model characterizing the biophysics of individual neurons. PMID:26651756

  2. Reexamination of Statistical Methods for Comparative Anatomy: Examples of Its Application and Comparisons with Other Parametric and Nonparametric Statistics

    PubMed Central

    Aversi-Ferreira, Roqueline A. G. M. F.; Nishijo, Hisao; Aversi-Ferreira, Tales Alexandre

    2015-01-01

    Various statistical methods have been published for comparative anatomy. However, few studies compared parametric and nonparametric statistical methods. Moreover, some previous studies using statistical method for comparative anatomy (SMCA) proposed the formula for comparison of groups of anatomical structures (multiple structures) among different species. The present paper described the usage of SMCA and compared the results by SMCA with those by parametric test (t-test) and nonparametric analyses (cladistics) of anatomical data. In conclusion, the SMCA can offer a more exact and precise way to compare single and multiple anatomical structures across different species, which requires analyses of nominal features in comparative anatomy. PMID:26413553

  3. Reexamination of Statistical Methods for Comparative Anatomy: Examples of Its Application and Comparisons with Other Parametric and Nonparametric Statistics.

    PubMed

    Aversi-Ferreira, Roqueline A G M F; Nishijo, Hisao; Aversi-Ferreira, Tales Alexandre

    2015-01-01

    Various statistical methods have been published for comparative anatomy. However, few studies compared parametric and nonparametric statistical methods. Moreover, some previous studies using statistical method for comparative anatomy (SMCA) proposed the formula for comparison of groups of anatomical structures (multiple structures) among different species. The present paper described the usage of SMCA and compared the results by SMCA with those by parametric test (t-test) and nonparametric analyses (cladistics) of anatomical data. In conclusion, the SMCA can offer a more exact and precise way to compare single and multiple anatomical structures across different species, which requires analyses of nominal features in comparative anatomy. PMID:26413553

  4. Emperical Laws in Economics Uncovered Using Methods in Statistical Mechanics

    NASA Astrophysics Data System (ADS)

    Stanley, H. Eugene

    2001-06-01

    In recent years, statistical physicists and computational physicists have determined that physical systems which consist of a large number of interacting particles obey universal "scaling laws" that serve to demonstrate an intrinsic self-similarity operating in such systems. Further, the parameters appearing in these scaling laws appear to be largely independent of the microscopic details. Since economic systems also consist of a large number of interacting units, it is plausible that scaling theory can be usefully applied to economics. To test this possibility using realistic data sets, a number of scientists have begun analyzing economic data using methods of statistical physics [1]. We have found evidence for scaling (and data collapse), as well as universality, in various quantities, and these recent results will be reviewed in this talk--starting with the most recent study [2]. We also propose models that may lead to some insight into these phenomena. These results will be discussed, as well as the overall rationale for why one might expect scaling principles to hold for complex economic systems. This work on which this talk is based is supported by BP, and was carried out in collaboration with L. A. N. Amaral S. V. Buldyrev, D. Canning, P. Cizeau, X. Gabaix, P. Gopikrishnan, S. Havlin, Y. Lee, Y. Liu, R. N. Mantegna, K. Matia, M. Meyer, C.-K. Peng, V. Plerou, M. A. Salinger, and M. H. R. Stanley. [1.] See, e.g., R. N. Mantegna and H. E. Stanley, Introduction to Econophysics: Correlations & Complexity in Finance (Cambridge University Press, Cambridge, 1999). [2.] P. Gopikrishnan, B. Rosenow, V. Plerou, and H. E. Stanley, "Identifying Business Sectors from Stock Price Fluctuations," e-print cond-mat/0011145; V. Plerou, P. Gopikrishnan, L. A. N. Amaral, X. Gabaix, and H. E. Stanley, "Diffusion and Economic Fluctuations," Phys. Rev. E (Rapid Communications) 62, 3023-3026 (2000); P. Gopikrishnan, V. Plerou, X. Gabaix, and H. E. Stanley, "Statistical Properties of

  5. Statistical methods for detecting periodic fragments in DNA sequence data

    PubMed Central

    2011-01-01

    Background Period 10 dinucleotides are structurally and functionally validated factors that influence the ability of DNA to form nucleosomes, histone core octamers. Robust identification of periodic signals in DNA sequences is therefore required to understand nucleosome organisation in genomes. While various techniques for identifying periodic components in genomic sequences have been proposed or adopted, the requirements for such techniques have not been considered in detail and confirmatory testing for a priori specified periods has not been developed. Results We compared the estimation accuracy and suitability for confirmatory testing of autocorrelation, discrete Fourier transform (DFT), integer period discrete Fourier transform (IPDFT) and a previously proposed Hybrid measure. A number of different statistical significance procedures were evaluated but a blockwise bootstrap proved superior. When applied to synthetic data whose period-10 signal had been eroded, or for which the signal was approximately period-10, the Hybrid technique exhibited superior properties during exploratory period estimation. In contrast, confirmatory testing using the blockwise bootstrap procedure identified IPDFT as having the greatest statistical power. These properties were validated on yeast sequences defined from a ChIP-chip study where the Hybrid metric confirmed the expected dominance of period-10 in nucleosome associated DNA but IPDFT identified more significant occurrences of period-10. Application to the whole genomes of yeast and mouse identified ~ 21% and ~ 19% respectively of these genomes as spanned by period-10 nucleosome positioning sequences (NPS). Conclusions For estimating the dominant period, we find the Hybrid period estimation method empirically to be the most effective for both eroded and approximate periodicity. The blockwise bootstrap was found to be effective as a significance measure, performing particularly well in the problem of period detection in the

  6. Methods in probability and statistical inference. Final report, June 15, 1975-June 30, 1979. [Dept. of Statistics, Univ. of Chicago

    SciTech Connect

    Wallace, D L; Perlman, M D

    1980-06-01

    This report describes the research activities of the Department of Statistics, University of Chicago, during the period June 15, 1975 to July 30, 1979. Nine research projects are briefly described on the following subjects: statistical computing and approximation techniques in statistics; numerical computation of first passage distributions; probabilities of large deviations; combining independent tests of significance; small-sample efficiencies of tests and estimates; improved procedures for simultaneous estimation and testing of many correlations; statistical computing and improved regression methods; comparison of several populations; and unbiasedness in multivariate statistics. A description of the statistical consultation activities of the Department that are of interest to DOE, in particular, the scientific interactions between the Department and the scientists at Argonne National Laboratories, is given. A list of publications issued during the term of the contract is included.

  7. Statistical methods for texture analysis applied to agronomical images

    NASA Astrophysics Data System (ADS)

    Cointault, F.; Journaux, L.; Gouton, P.

    2008-02-01

    For activities of agronomical research institute, the land experimentations are essential and provide relevant information on crops such as disease rate, yield components, weed rate... Generally accurate, they are manually done and present numerous drawbacks, such as penibility, notably for wheat ear counting. In this case, the use of color and/or texture image processing to estimate the number of ears per square metre can be an improvement. Then, different image segmentation techniques based on feature extraction have been tested using textural information with first and higher order statistical methods. The Run Length method gives the best results closed to manual countings with an average error of 3%. Nevertheless, a fine justification of hypothesis made on the values of the classification and description parameters is necessary, especially for the number of classes and the size of analysis windows, through the estimation of a cluster validity index. The first results show that the mean number of classes in wheat image is of 11, which proves that our choice of 3 is not well adapted. To complete these results, we are currently analysing each of the class previously extracted to gather together all the classes characterizing the ears.

  8. System Synthesis in Preliminary Aircraft Design using Statistical Methods

    NASA Technical Reports Server (NTRS)

    DeLaurentis, Daniel; Mavris, Dimitri N.; Schrage, Daniel P.

    1996-01-01

    This paper documents an approach to conceptual and preliminary aircraft design in which system synthesis is achieved using statistical methods, specifically design of experiments (DOE) and response surface methodology (RSM). These methods are employed in order to more efficiently search the design space for optimum configurations. In particular, a methodology incorporating three uses of these techniques is presented. First, response surface equations are formed which represent aerodynamic analyses, in the form of regression polynomials, which are more sophisticated than generally available in early design stages. Next, a regression equation for an overall evaluation criterion is constructed for the purpose of constrained optimization at the system level. This optimization, though achieved in a innovative way, is still traditional in that it is a point design solution. The methodology put forward here remedies this by introducing uncertainty into the problem, resulting a solutions which are probabilistic in nature. DOE/RSM is used for the third time in this setting. The process is demonstrated through a detailed aero-propulsion optimization of a high speed civil transport. Fundamental goals of the methodology, then, are to introduce higher fidelity disciplinary analyses to the conceptual aircraft synthesis and provide a roadmap for transitioning from point solutions to probabalistic designs (and eventually robust ones).

  9. System Synthesis in Preliminary Aircraft Design Using Statistical Methods

    NASA Technical Reports Server (NTRS)

    DeLaurentis, Daniel; Mavris, Dimitri N.; Schrage, Daniel P.

    1996-01-01

    This paper documents an approach to conceptual and early preliminary aircraft design in which system synthesis is achieved using statistical methods, specifically Design of Experiments (DOE) and Response Surface Methodology (RSM). These methods are employed in order to more efficiently search the design space for optimum configurations. In particular, a methodology incorporating three uses of these techniques is presented. First, response surface equations are formed which represent aerodynamic analyses, in the form of regression polynomials, which are more sophisticated than generally available in early design stages. Next, a regression equation for an Overall Evaluation Criterion is constructed for the purpose of constrained optimization at the system level. This optimization, though achieved in an innovative way, is still traditional in that it is a point design solution. The methodology put forward here remedies this by introducing uncertainty into the problem, resulting in solutions which are probabilistic in nature. DOE/RSM is used for the third time in this setting. The process is demonstrated through a detailed aero-propulsion optimization of a High Speed Civil Transport. Fundamental goals of the methodology, then, are to introduce higher fidelity disciplinary analyses to the conceptual aircraft synthesis and provide a roadmap for transitioning from point solutions to probabilistic designs (and eventually robust ones).

  10. Hydrologic extremes - an intercomparison of multiple gridded statistical downscaling methods

    NASA Astrophysics Data System (ADS)

    Werner, A. T.; Cannon, A. J.

    2015-06-01

    Gridded statistical downscaling methods are the main means of preparing climate model data to drive distributed hydrological models. Past work on the validation of climate downscaling methods has focused on temperature and precipitation, with less attention paid to the ultimate outputs from hydrological models. Also, as attention shifts towards projections of extreme events, downscaling comparisons now commonly assess methods in terms of climate extremes, but hydrologic extremes are less well explored. Here, we test the ability of gridded downscaling models to replicate historical properties of climate and hydrologic extremes, as measured in terms of temporal sequencing (i.e., correlation tests) and distributional properties (i.e., tests for equality of probability distributions). Outputs from seven downscaling methods - bias correction constructed analogues (BCCA), double BCCA (DBCCA), BCCA with quantile mapping reordering (BCCAQ), bias correction spatial disaggregation (BCSD), BCSD using minimum/maximum temperature (BCSDX), climate imprint delta method (CI), and bias corrected CI (BCCI) - are used to drive the Variable Infiltration Capacity (VIC) model over the snow-dominated Peace River basin, British Columbia. Outputs are tested using split-sample validation on 26 climate extremes indices (ClimDEX) and two hydrologic extremes indices (3 day peak flow and 7 day peak flow). To characterize observational uncertainty, four atmospheric reanalyses are used as climate model surrogates and two gridded observational datasets are used as downscaling target data. The skill of the downscaling methods generally depended on reanalysis and gridded observational dataset. However, CI failed to reproduce the distribution and BCSD and BCSDX the timing of winter 7 day low flow events, regardless of reanalysis or observational dataset. Overall, DBCCA passed the greatest number of tests for the ClimDEX indices, while BCCAQ, which is designed to more accurately resolve event

  11. Hydrologic extremes - an intercomparison of multiple gridded statistical downscaling methods

    NASA Astrophysics Data System (ADS)

    Werner, Arelia T.; Cannon, Alex J.

    2016-04-01

    Gridded statistical downscaling methods are the main means of preparing climate model data to drive distributed hydrological models. Past work on the validation of climate downscaling methods has focused on temperature and precipitation, with less attention paid to the ultimate outputs from hydrological models. Also, as attention shifts towards projections of extreme events, downscaling comparisons now commonly assess methods in terms of climate extremes, but hydrologic extremes are less well explored. Here, we test the ability of gridded downscaling models to replicate historical properties of climate and hydrologic extremes, as measured in terms of temporal sequencing (i.e. correlation tests) and distributional properties (i.e. tests for equality of probability distributions). Outputs from seven downscaling methods - bias correction constructed analogues (BCCA), double BCCA (DBCCA), BCCA with quantile mapping reordering (BCCAQ), bias correction spatial disaggregation (BCSD), BCSD using minimum/maximum temperature (BCSDX), the climate imprint delta method (CI), and bias corrected CI (BCCI) - are used to drive the Variable Infiltration Capacity (VIC) model over the snow-dominated Peace River basin, British Columbia. Outputs are tested using split-sample validation on 26 climate extremes indices (ClimDEX) and two hydrologic extremes indices (3-day peak flow and 7-day peak flow). To characterize observational uncertainty, four atmospheric reanalyses are used as climate model surrogates and two gridded observational data sets are used as downscaling target data. The skill of the downscaling methods generally depended on reanalysis and gridded observational data set. However, CI failed to reproduce the distribution and BCSD and BCSDX the timing of winter 7-day low-flow events, regardless of reanalysis or observational data set. Overall, DBCCA passed the greatest number of tests for the ClimDEX indices, while BCCAQ, which is designed to more accurately resolve event

  12. Equivalence Class Formation: A Method for Teaching Statistical Interactions

    ERIC Educational Resources Information Center

    Fields, Lanny; Travis, Robert; Roy, Deborah; Yadlovker, Eytan; de Aguiar-Rocha, Liliane; Sturmey, Peter

    2009-01-01

    Many students struggle with statistical concepts such as interaction. In an experimental group, participants took a paper-and-pencil test and then were given training to establish equivalent classes containing four different statistical interactions. All participants formed the equivalence classes and showed maintenance when probes contained novel…

  13. A Statistical Method for Quantifying Songbird Phonology and Syntax

    PubMed Central

    Wu, Wei; Thompson, John A.; Bertram, Richard; Johnson, Frank

    2008-01-01

    Songbirds are the preeminent animal model for understanding how the brain encodes and produces learned vocalizations. Here, we report a new statistical method, the Kullback-Leibler (K-L) distance, for analyzing vocal change over time. First, we use a computerized recording system to capture all song syllables produced by birds each day. Sound Analysis Pro software (Tchernichovski et al., 2000) is then used to measure the duration of each syllable as well as four spectral features: pitch, entropy, frequency modulation, and pitch goodness. Next, 2-dimensional scatter plots of each day of singing are created where syllable duration is on the x-axis and each of the spectral features is represented separately on the y-axis. Each point in the scatter plots represents one syllable and we regard these plots as random samples from a probability distribution. We then apply the standard information-theoretic quantity K-L distance to measure dissimilarity in phonology across days of singing. A variant of this procedure can also be used to analyze differences in syllable syntax. PMID:18674560

  14. A statistical method for draft tube pressure pulsation analysis

    NASA Astrophysics Data System (ADS)

    Doerfler, P. K.; Ruchonnet, N.

    2012-11-01

    Draft tube pressure pulsation (DTPP) in Francis turbines is composed of various components originating from different physical phenomena. These components may be separated because they differ by their spatial relationships and by their propagation mechanism. The first step for such an analysis was to distinguish between so-called synchronous and asynchronous pulsations; only approximately periodic phenomena could be described in this manner. However, less regular pulsations are always present, and these become important when turbines have to operate in the far off-design range, in particular at very low load. The statistical method described here permits to separate the stochastic (random) component from the two traditional 'regular' components. It works in connection with the standard technique of model testing with several pressure signals measured in draft tube cone. The difference between the individual signals and the averaged pressure signal, together with the coherence between the individual pressure signals is used for analysis. An example reveals that a generalized, non-periodic version of the asynchronous pulsation is important at low load.

  15. Asbestos/NESHAP adequately wet guidance

    SciTech Connect

    Shafer, R.; Throwe, S.; Salgado, O.; Garlow, C.; Hoerath, E.

    1990-12-01

    The Asbestos NESHAP requires facility owners and/or operators involved in demolition and renovation activities to control emissions of particulate asbestos to the outside air because no safe concentration of airborne asbestos has ever been established. The primary method used to control asbestos emissions is to adequately wet the Asbestos Containing Material (ACM) with a wetting agent prior to, during and after demolition/renovation activities. The purpose of the document is to provide guidance to asbestos inspectors and the regulated community on how to determine if friable ACM is adequately wet as required by the Asbestos NESHAP.

  16. Debating Curricular Strategies for Teaching Statistics and Research Methods: What Does the Current Evidence Suggest?

    ERIC Educational Resources Information Center

    Barron, Kenneth E.; Apple, Kevin J.

    2014-01-01

    Coursework in statistics and research methods is a core requirement in most undergraduate psychology programs. However, is there an optimal way to structure and sequence methodology courses to facilitate student learning? For example, should statistics be required before research methods, should research methods be required before statistics, or…

  17. Teaching biology through statistics: application of statistical methods in genetics and zoology courses.

    PubMed

    Colon-Berlingeri, Migdalisel; Burrowes, Patricia A

    2011-01-01

    Incorporation of mathematics into biology curricula is critical to underscore for undergraduate students the relevance of mathematics to most fields of biology and the usefulness of developing quantitative process skills demanded in modern biology. At our institution, we have made significant changes to better integrate mathematics into the undergraduate biology curriculum. The curricular revision included changes in the suggested course sequence, addition of statistics and precalculus as prerequisites to core science courses, and incorporating interdisciplinary (math-biology) learning activities in genetics and zoology courses. In this article, we describe the activities developed for these two courses and the assessment tools used to measure the learning that took place with respect to biology and statistics. We distinguished the effectiveness of these learning opportunities in helping students improve their understanding of the math and statistical concepts addressed and, more importantly, their ability to apply them to solve a biological problem. We also identified areas that need emphasis in both biology and mathematics courses. In light of our observations, we recommend best practices that biology and mathematics academic departments can implement to train undergraduates for the demands of modern biology. PMID:21885822

  18. FASTLens (FAst STatistics for weak Lensing): Fast Method for Weak Lensing Statistics and Map Making

    NASA Astrophysics Data System (ADS)

    Pires, S.; Starck, J.-L.; Amara, A.; Teyssier, R.; Refregier, A.; Fadili, J.

    2010-10-01

    The analysis of weak lensing data requires to account for missing data such as masking out of bright stars. To date, the majority of lensing analyses uses the two point-statistics of the cosmic shear field. These can either be studied directly using the two-point correlation function, or in Fourier space, using the power spectrum. The two-point correlation function is unbiased by missing data but its direct calculation will soon become a burden with the exponential growth of astronomical data sets. The power spectrum is fast to estimate but a mask correction should be estimated. Other statistics can be used but these are strongly sensitive to missing data. The solution that is proposed by FASTLens is to properly fill-in the gaps with only NlogN operations, leading to a complete weak lensing mass map from which one can compute straight forwardly and with a very good accuracy any kind of statistics like power spectrum or bispectrum.

  19. Teaching Biology through Statistics: Application of Statistical Methods in Genetics and Zoology Courses

    PubMed Central

    Colon-Berlingeri, Migdalisel; Burrowes, Patricia A.

    2011-01-01

    Incorporation of mathematics into biology curricula is critical to underscore for undergraduate students the relevance of mathematics to most fields of biology and the usefulness of developing quantitative process skills demanded in modern biology. At our institution, we have made significant changes to better integrate mathematics into the undergraduate biology curriculum. The curricular revision included changes in the suggested course sequence, addition of statistics and precalculus as prerequisites to core science courses, and incorporating interdisciplinary (math–biology) learning activities in genetics and zoology courses. In this article, we describe the activities developed for these two courses and the assessment tools used to measure the learning that took place with respect to biology and statistics. We distinguished the effectiveness of these learning opportunities in helping students improve their understanding of the math and statistical concepts addressed and, more importantly, their ability to apply them to solve a biological problem. We also identified areas that need emphasis in both biology and mathematics courses. In light of our observations, we recommend best practices that biology and mathematics academic departments can implement to train undergraduates for the demands of modern biology. PMID:21885822

  20. Statistics.

    PubMed

    1993-02-01

    In 1984, 99% of abortions conducted in Bombay, India, were of female fetuses. In 1986-87, 30,000-50,000 female fetuses were aborted in India. In 1987-88, 7 Delhi clinics conducted 13,000 sex determination tests. Thus, discrimination against females begins before birth in India. Some states (Maharashtra, Goa, and Gujarat) have drafted legislation to prevent the use of prenatal diagnostic tests (e.g., ultrasonography) for sex determination purposes. Families make decisions about an infant's nutrition based on the infant's sex so it is not surprising to see a higher incidence of morbidity among girls than boys (e.g., for respiratory infections in 1985, 55.5% vs. 27.3%). Consequently, they are more likely to die than boys. Even though vasectomy is simpler and safer than tubectomy, the government promotes female sterilizations. The percentage of all sexual sterilizations being tubectomy has increased steadily from 84% to 94% (1986-90). Family planning programs focus on female contraceptive methods, despite the higher incidence of adverse health effects from female methods (e.g., IUD causes pain and heavy bleeding). Some women advocates believe the effects to be so great that India should ban contraceptives and injectable contraceptives. The maternal mortality rate is quite high (460/100,000 live births), equaling a lifetime risk of 1:18 of a pregnancy-related death. 70% of these maternal deaths are preventable. Leading causes of maternal deaths in India are anemia, hemorrhage, eclampsia, sepsis, and abortion. Most pregnant women do not receive prenatal care. Untrained personnel attend about 70% of deliveries in rural areas and 29% in urban areas. Appropriate health services and other interventions would prevent the higher age specific death rates for females between 0 and 35 years old. Even though the government does provide maternal and child health services, it needs to stop decreasing resource allocate for health and start increasing it. PMID:12286355

  1. Statistical methods of combining information: Applications to sensor data fusion

    SciTech Connect

    Burr, T.

    1996-12-31

    This paper reviews some statistical approaches to combining information from multiple sources. Promising new approaches will be described, and potential applications to combining not-so-different data sources such as sensor data will be discussed. Experiences with one real data set are described.

  2. Basic Statistical Concepts and Methods for Earth Scientists

    USGS Publications Warehouse

    Olea, Ricardo A.

    2008-01-01

    INTRODUCTION Statistics is the science of collecting, analyzing, interpreting, modeling, and displaying masses of numerical data primarily for the characterization and understanding of incompletely known systems. Over the years, these objectives have lead to a fair amount of analytical work to achieve, substantiate, and guide descriptions and inferences.

  3. Critical Realism and Statistical Methods--A Response to Nash

    ERIC Educational Resources Information Center

    Scott, David

    2007-01-01

    This article offers a defence of critical realism in the face of objections Nash (2005) makes to it in a recent edition of this journal. It is argued that critical and scientific realisms are closely related and that both are opposed to statistical positivism. However, the suggestion is made that scientific realism retains (from statistical…

  4. Accountability Indicators from the Viewpoint of Statistical Method.

    ERIC Educational Resources Information Center

    Jordan, Larry

    Few people seriously regard students as "products" coming off an educational assembly line, but notions about accountability and quality improvement in higher education are pervaded by manufacturing ideas and metaphors. Because numerical indicators of quality are inevitably expressed by trend lines or statistical control chars of some kind, they…

  5. Modification of codes NUALGAM and BREMRAD. Volume 3: Statistical considerations of the Monte Carlo method

    NASA Technical Reports Server (NTRS)

    Firstenberg, H.

    1971-01-01

    The statistics are considered of the Monte Carlo method relative to the interpretation of the NUGAM2 and NUGAM3 computer code results. A numerical experiment using the NUGAM2 code is presented and the results are statistically interpreted.

  6. Statistical Methods for Rapid Aerothermal Analysis and Design Technology

    NASA Technical Reports Server (NTRS)

    Morgan, Carolyn; DePriest, Douglas; Thompson, Richard (Technical Monitor)

    2002-01-01

    The cost and safety goals for NASA's next generation of reusable launch vehicle (RLV) will require that rapid high-fidelity aerothermodynamic design tools be used early in the design cycle. To meet these requirements, it is desirable to establish statistical models that quantify and improve the accuracy, extend the applicability, and enable combined analyses using existing prediction tools. The research work was focused on establishing the suitable mathematical/statistical models for these purposes. It is anticipated that the resulting models can be incorporated into a software tool to provide rapid, variable-fidelity, aerothermal environments to predict heating along an arbitrary trajectory. This work will support development of an integrated design tool to perform automated thermal protection system (TPS) sizing and material selection.

  7. Spatial Statistics Preserving Interpolation Methods for Estimation of Missing Precipitation Data

    NASA Astrophysics Data System (ADS)

    El Sharif, H.; Teegavarapu, R. S.

    2011-12-01

    Spatial interpolation methods used for estimation of missing precipitation data at a site seldom check for their ability to preserve site and regional statistics. Such statistics are primarily defined by spatial correlations and other site-to-site statistics in a region. Preservation of site and regional statistics represents a means of assessing the validity of missing precipitation estimates at a site. This study will evaluate the efficacy of traditional deterministic and stochastic interpolation methods aimed at estimation of missing data in preserving site and regional statistics. New optimal spatial interpolation methods that are intended to preserve these statistics are also proposed and evaluated in this study. Rain gauge sites in the state of Kentucky, USA, are used as a case study for evaluation of existing and newly proposed methods. Several error and performance measures will be used to evaluate the methods and trade-offs in accuracy of estimation and preservation of site and regional statistics.

  8. Applying Statistical Methods To The Proton Radius Puzzle

    NASA Astrophysics Data System (ADS)

    Higinbotham, Douglas

    2016-03-01

    In recent nuclear physics publications, one can find many examples where chi2 and reduced chi2 are the only tools used for the selection of models even though a chi2 difference test is only meaningful for nested models. With this in mind, we reanalyze electron scattering data, being careful to clearly define our selection criteria as well as using a co-variance matrix and confidence levels as per the statistics section of the particle data book. We will show that when applying such techniques to hydrogen elastic scattering data, the nested models often require fewer parameters than typically used and that non-nested models are often rejected inappropriately.

  9. Research design and statistical methods in Pakistan Journal of Medical Sciences (PJMS)

    PubMed Central

    Akhtar, Sohail; Shah, Syed Wadood Ali; Rafiq, M.; Khan, Ajmal

    2016-01-01

    Objective: This article compares the study design and statistical methods used in 2005, 2010 and 2015 of Pakistan Journal of Medical Sciences (PJMS). Methods: Only original articles of PJMS were considered for the analysis. The articles were carefully reviewed for statistical methods and designs, and then recorded accordingly. The frequency of each statistical method and research design was estimated and compared with previous years. Results: A total of 429 articles were evaluated (n=74 in 2005, n=179 in 2010, n=176 in 2015) in which 171 (40%) were cross-sectional and 116 (27%) were prospective study designs. A verity of statistical methods were found in the analysis. The most frequent methods include: descriptive statistics (n=315, 73.4%), chi-square/Fisher’s exact tests (n=205, 47.8%) and student t-test (n=186, 43.4%). There was a significant increase in the use of statistical methods over time period: t-test, chi-square/Fisher’s exact test, logistic regression, epidemiological statistics, and non-parametric tests. Conclusion: This study shows that a diverse variety of statistical methods have been used in the research articles of PJMS and frequency improved from 2005 to 2015. However, descriptive statistics was the most frequent method of statistical analysis in the published articles while cross-sectional study design was common study design. PMID:27022365

  10. Statistical methods for the analysis of climate extremes

    NASA Astrophysics Data System (ADS)

    Naveau, Philippe; Nogaj, Marta; Ammann, Caspar; Yiou, Pascal; Cooley, Daniel; Jomelli, Vincent

    2005-08-01

    Currently there is an increasing research activity in the area of climate extremes because they represent a key manifestation of non-linear systems and an enormous impact on economic and social human activities. Our understanding of the mean behavior of climate and its 'normal' variability has been improving significantly during the last decades. In comparison, climate extreme events have been hard to study and even harder to predict because they are, by definition, rare and obey different statistical laws than averages. In this context, the motivation for this paper is twofold. Firstly, we recall the basic principles of Extreme Value Theory that is used on a regular basis in finance and hydrology, but it still does not have the same success in climate studies. More precisely, the theoretical distributions of maxima and large peaks are recalled. The parameters of such distributions are estimated with the maximum likelihood estimation procedure that offers the flexibility to take into account explanatory variables in our analysis. Secondly, we detail three case-studies to show that this theory can provide a solid statistical foundation, specially when assessing the uncertainty associated with extreme events in a wide range of applications linked to the study of our climate. To cite this article: P. Naveau et al., C. R. Geoscience 337 (2005).

  11. Students' Attitudes toward Statistics across the Disciplines: A Mixed-Methods Approach

    ERIC Educational Resources Information Center

    Griffith, James D.; Adams, Lea T.; Gu, Lucy L.; Hart, Christian L.; Nichols-Whitehead, Penney

    2012-01-01

    Students' attitudes toward statistics were investigated using a mixed-methods approach including a discovery-oriented qualitative methodology among 684 undergraduate students across business, criminal justice, and psychology majors where at least one course in statistics was required. Students were asked about their attitudes toward statistics and…

  12. Counting Better? An Examination of the Impact of Quantitative Method Teaching on Statistical Anxiety and Confidence

    ERIC Educational Resources Information Center

    Chamberlain, John Martyn; Hillier, John; Signoretta, Paola

    2015-01-01

    This article reports the results of research concerned with students' statistical anxiety and confidence to both complete and learn to complete statistical tasks. Data were collected at the beginning and end of a quantitative method statistics module. Students recognised the value of numeracy skills but felt they were not necessarily relevant for…

  13. Statistical Methods and Tools for Hanford Staged Feed Tank Sampling

    SciTech Connect

    Fountain, Matthew S.; Brigantic, Robert T.; Peterson, Reid A.

    2013-10-01

    This report summarizes work conducted by Pacific Northwest National Laboratory to technically evaluate the current approach to staged feed sampling of high-level waste (HLW) sludge to meet waste acceptance criteria (WAC) for transfer from tank farms to the Hanford Waste Treatment and Immobilization Plant (WTP). The current sampling and analysis approach is detailed in the document titled Initial Data Quality Objectives for WTP Feed Acceptance Criteria, 24590-WTP-RPT-MGT-11-014, Revision 0 (Arakali et al. 2011). The goal of this current work is to evaluate and provide recommendations to support a defensible, technical and statistical basis for the staged feed sampling approach that meets WAC data quality objectives (DQOs).

  14. Statistical methods and neural network approaches for classification of data from multiple sources

    NASA Technical Reports Server (NTRS)

    Benediktsson, Jon Atli; Swain, Philip H.

    1990-01-01

    Statistical methods for classification of data from multiple data sources are investigated and compared to neural network models. A problem with using conventional multivariate statistical approaches for classification of data of multiple types is in general that a multivariate distribution cannot be assumed for the classes in the data sources. Another common problem with statistical classification methods is that the data sources are not equally reliable. This means that the data sources need to be weighted according to their reliability but most statistical classification methods do not have a mechanism for this. This research focuses on statistical methods which can overcome these problems: a method of statistical multisource analysis and consensus theory. Reliability measures for weighting the data sources in these methods are suggested and investigated. Secondly, this research focuses on neural network models. The neural networks are distribution free since no prior knowledge of the statistical distribution of the data is needed. This is an obvious advantage over most statistical classification methods. The neural networks also automatically take care of the problem involving how much weight each data source should have. On the other hand, their training process is iterative and can take a very long time. Methods to speed up the training procedure are introduced and investigated. Experimental results of classification using both neural network models and statistical methods are given, and the approaches are compared based on these results.

  15. Statistical energy analysis response prediction methods for structural systems

    NASA Technical Reports Server (NTRS)

    Davis, R. F.

    1979-01-01

    The results of an effort to document methods for accomplishing response predictions for commonly encountered aerospace structural configurations is presented. Application of these methods to specified aerospace structure to provide sample analyses is included. An applications manual, with the structural analyses appended as example problems is given. Comparisons of the response predictions with measured data are provided for three of the example problems.

  16. Data Analysis & Statistical Methods for Command File Errors

    NASA Technical Reports Server (NTRS)

    Meshkat, Leila; Waggoner, Bruce; Bryant, Larry

    2014-01-01

    This paper explains current work on modeling for managing the risk of command file errors. It is focused on analyzing actual data from a JPL spaceflight mission to build models for evaluating and predicting error rates as a function of several key variables. We constructed a rich dataset by considering the number of errors, the number of files radiated, including the number commands and blocks in each file, as well as subjective estimates of workload and operational novelty. We have assessed these data using different curve fitting and distribution fitting techniques, such as multiple regression analysis, and maximum likelihood estimation to see how much of the variability in the error rates can be explained with these. We have also used goodness of fit testing strategies and principal component analysis to further assess our data. Finally, we constructed a model of expected error rates based on the what these statistics bore out as critical drivers to the error rate. This model allows project management to evaluate the error rate against a theoretically expected rate as well as anticipate future error rates.

  17. Statistical method for resolving the photon-photoelectron-counting inversion problem

    SciTech Connect

    Wu Jinlong; Li Tiejun; Peng, Xiang; Guo Hong

    2011-02-01

    A statistical inversion method is proposed for the photon-photoelectron-counting statistics in quantum key distribution experiment. With the statistical viewpoint, this problem is equivalent to the parameter estimation for an infinite binomial mixture model. The coarse-graining idea and Bayesian methods are applied to deal with this ill-posed problem, which is a good simple example to show the successful application of the statistical methods to the inverse problem. Numerical results show the applicability of the proposed strategy. The coarse-graining idea for the infinite mixture models should be general to be used in the future.

  18. Agreement between Statistical and Judgmental Item Bias Methods.

    ERIC Educational Resources Information Center

    Rengel, Elizabeth

    The Ball Aptitude Battery (BAB) was examined for item bias in a sample of 577 high school students in which males and females, as well as three ethnic groups (Blacks, Whites, and Hispanics) were represented. The objectives of the investigation were: (1) to assess the level of interrater agreement for the judgmental method; (2) to find the level of…

  19. Scalar Product Method in Statistical Mechanics of Boundary Tension

    NASA Astrophysics Data System (ADS)

    Cenedese, Pierre; Kikuchi, Ryoichi

    1997-02-01

    The interphase excess free energy σ due to an interphase boundary (IPB) is calculated in the Ising model using the Scalar Product (SP) method. Different from the “sum” method calculation of σ based on the boundary profile, the SP approach skips the profile and directly evaluates σ from the equilibrium properties of the homogeneous phases meeting at the boundary. Using a series of Cluster Variation Method (CVM) approximations of the basic cluster size n, a series of σ (n) values are calculated. For the 2-D square lattice, the limit of the SP σ (n) for nrightarrow infty is very close to the exact value of Onsager for the <~ngle 10rangle orientation and to that of Fisher and Ferdinand for <~ngle 10rangle. Similar extrapolation was done for the 3-D simple cubic lattice. The result agrees well with the known Monte Carlo results. Because the SP approach does not calculate the profile, computational time and labor are much less than those of the sum method.

  20. Statistical Signal Processing Methods in Scattering and Imaging

    NASA Astrophysics Data System (ADS)

    Zambrano Nunez, Maytee

    of projective measurements of the field. The projective measurements are implemented using spatial light modulators of the digital micromirror device (DMD) family, followed by a geometrical-optics-based image casting system to capture the data using a single photodetector. The reconstruction process is based on the new field of compressive sensing which allows, thanks to the exploitation of statistical priors such as sparsity, the imaging of the main features of the objects under illumination with much less data than a typical CCD camera. The present system expands the scope of single-detector imaging systems based on compressive sensing from the incoherent light regime, which has been the past focus, to the coherent light regime which is key in many biomedical and Homeland security applications (THz imaging).

  1. Relationship between Students' Scores on Research Methods and Statistics, and Undergraduate Project Scores

    ERIC Educational Resources Information Center

    Ossai, Peter Agbadobi Uloku

    2016-01-01

    This study examined the relationship between students' scores on Research Methods and statistics, and undergraduate project at the final year. The purpose was to find out whether students matched knowledge of research with project-writing skill. The study adopted an expost facto correlational design. Scores on Research Methods and Statistics for…

  2. APA's Learning Objectives for Research Methods and Statistics in Practice: A Multimethod Analysis

    ERIC Educational Resources Information Center

    Tomcho, Thomas J.; Rice, Diana; Foels, Rob; Folmsbee, Leah; Vladescu, Jason; Lissman, Rachel; Matulewicz, Ryan; Bopp, Kara

    2009-01-01

    Research methods and statistics courses constitute a core undergraduate psychology requirement. We analyzed course syllabi and faculty self-reported coverage of both research methods and statistics course learning objectives to assess the concordance with APA's learning objectives (American Psychological Association, 2007). We obtained a sample of…

  3. Best Practices in Teaching Statistics and Research Methods in the Behavioral Sciences [with CD-ROM

    ERIC Educational Resources Information Center

    Dunn, Dana S., Ed.; Smith, Randolph A., Ed.; Beins, Barney, Ed.

    2007-01-01

    This book provides a showcase for "best practices" in teaching statistics and research methods in two- and four-year colleges and universities. A helpful resource for teaching introductory, intermediate, and advanced statistics and/or methods, the book features coverage of: (1) ways to integrate these courses; (2) how to promote ethical conduct;…

  4. A REVIEW OF STATISTICAL METHODS FOR THE METEOROLOGICAL ADJUSTMENT OF TROPOSPHERIC OZONE

    EPA Science Inventory

    A variety of statistical methods for meteorological adjustment of ozone have been proposed in the literature over the last decade for purposes of forecasting, estimating ozone time trends, or investigating underlying mechanisms from an empirical perspective. The methods can be...

  5. Statistical classification methods for estimating ancestry using morphoscopic traits.

    PubMed

    Hefner, Joseph T; Ousley, Stephen D

    2014-07-01

    Ancestry assessments using cranial morphoscopic traits currently rely on subjective trait lists and observer experience rather than empirical support. The trait list approach, which is untested, unverified, and in many respects unrefined, is relied upon because of tradition and subjective experience. Our objective was to examine the utility of frequently cited morphoscopic traits and to explore eleven appropriate and novel methods for classifying an unknown cranium into one of several reference groups. Based on these results, artificial neural networks (aNNs), OSSA, support vector machines, and random forest models showed mean classification accuracies of at least 85%. The aNNs had the highest overall classification rate (87.8%), and random forests show the smallest difference between the highest (90.4%) and lowest (76.5%) classification accuracies. The results of this research demonstrate that morphoscopic traits can be successfully used to assess ancestry without relying only on the experience of the observer. PMID:24646108

  6. Predicting sulphur and nitrogen deposition using a simple statistical method

    NASA Astrophysics Data System (ADS)

    Filip, Oulehle; Jiří, Kopáček; Tomáš, Chuman; Vladimír, Černohous; Iva, Hůnová; Jakub, Hruška; Pavel, Krám; Zora, Lachmanová; Tomáš, Navrátil; Petr, Štěpánek; Miroslav, Tesař; Christopher, Evans D.

    2016-09-01

    Data from 32 long-term (1994-2012) monitoring sites were used to assess temporal development and spatial variability of sulphur (S) and inorganic nitrogen (N) concentrations in bulk precipitation, and S in throughfall, for the Czech Republic. Despite large variance in absolute S and N concentration/deposition among sites, temporal coherence using standardised data (Z score) was demonstrated. Overall significant declines of SO4 concentration in bulk and throughfall precipitation, as well as NO3 and NH4 concentration in bulk precipitation, were observed. Median Z score values of bulk SO4, NO3 and NH4 and throughfall SO4 derived from observations and the respective emission rates of SO2, NOx and NH3 in the Czech Republic and Slovakia showed highly significant (p < 0.001) relationships. Using linear regression models, Z score values were calculated for the whole period 1900-2012 and then back-transformed to give estimates of concentration for the individual sites. Uncertainty associated with the concentration calculations was estimated as 20% for SO4 bulk precipitation, 22% for throughfall SO4, 18% for bulk NO3 and 28% for bulk NH4. The application of the method suggested that it is effective in the long-term reconstruction and prediction of S and N deposition at a variety of sites. Multiple regression modelling was used to extrapolate site characteristics (mean precipitation chemistry and its standard deviation) from monitored to unmonitored sites. Spatially distributed temporal development of S and N depositions were calculated since 1900. The method allows spatio-temporal estimation of the acid deposition in regions with extensive monitoring of precipitation chemistry.

  7. Statistical methods for the forensic analysis of striated tool marks

    SciTech Connect

    Hoeksema, Amy Beth

    2013-01-01

    In forensics, fingerprints can be used to uniquely identify suspects in a crime. Similarly, a tool mark left at a crime scene can be used to identify the tool that was used. However, the current practice of identifying matching tool marks involves visual inspection of marks by forensic experts which can be a very subjective process. As a result, declared matches are often successfully challenged in court, so law enforcement agencies are particularly interested in encouraging research in more objective approaches. Our analysis is based on comparisons of profilometry data, essentially depth contours of a tool mark surface taken along a linear path. In current practice, for stronger support of a match or non-match, multiple marks are made in the lab under the same conditions by the suspect tool. We propose the use of a likelihood ratio test to analyze the difference between a sample of comparisons of lab tool marks to a field tool mark, against a sample of comparisons of two lab tool marks. Chumbley et al. (2010) point out that the angle of incidence between the tool and the marked surface can have a substantial impact on the tool mark and on the effectiveness of both manual and algorithmic matching procedures. To better address this problem, we describe how the analysis can be enhanced to model the effect of tool angle and allow for angle estimation for a tool mark left at a crime scene. With sufficient development, such methods may lead to more defensible forensic analyses.

  8. Deep Mixing in Stellar Variability: Improved Method, Statistics, and Applications

    NASA Astrophysics Data System (ADS)

    Arkhypov, Oleksiy V.; Khodachenko, Maxim L.; Lammer, Helmut; Güdel, Manuel; Lüftinger, Theresa; Johnstone, Colin P.

    2016-07-01

    The preliminary results on deep-mixing manifestations in stellar variability are tested using our improved method and extended data set. We measure the timescales τ m of the stochastic change in the spectral power of rotational harmonics with numbers m ≤ 3 in the light curves of 1361 main-sequence stars from the Kepler mission archive. We find that the gradient [{log}({τ }2)-{log}({τ }1)]/[{log}(2)-{log}(1)] has a histogram maximum at ‑2/3, demonstrating agreement with Kolmogorov’s theory of turbulence and therefore confirming the manifestation of deep mixing. The squared amplitudes of the first and second rotational harmonics, corrected for integral photometry distortion, also show a quasi-Kolmogorov character with spectral index ≈‑5/3. Moreover, the reduction of τ 1 and τ 2 to the timescales τ lam1 and τ lam2 of laminar convection in the deep stellar layers reveals the proximity of both τ lam1 and τ lam2 to the turnover time τ MLT of standard mixing length theory. Considering this result, we use the obtained stellar variability timescales instead of τ MLT in our analysis of the relation between stellar activity and the Rossby number P/τ MLT. Comparison of our diagrams with previous results and theoretical expectations shows that best-fit correspondence is achieved for τ lam1, which can therefore be used as an analog of τ MLT. This means that the laminar component (giant cells) of stellar turbulent convection indeed plays an important role in the physics of stars. Additionally, we estimate the diffusivity of magnetic elements in stellar photospheres.

  9. 21 CFR 1404.900 - Adequate evidence.

    Code of Federal Regulations, 2010 CFR

    2010-04-01

    ... 21 Food and Drugs 9 2010-04-01 2010-04-01 false Adequate evidence. 1404.900 Section 1404.900 Food and Drugs OFFICE OF NATIONAL DRUG CONTROL POLICY GOVERNMENTWIDE DEBARMENT AND SUSPENSION (NONPROCUREMENT) Definitions § 1404.900 Adequate evidence. Adequate evidence means information sufficient to support the reasonable belief that a particular...

  10. 29 CFR 98.900 - Adequate evidence.

    Code of Federal Regulations, 2010 CFR

    2010-07-01

    ... 29 Labor 1 2010-07-01 2010-07-01 true Adequate evidence. 98.900 Section 98.900 Labor Office of the Secretary of Labor GOVERNMENTWIDE DEBARMENT AND SUSPENSION (NONPROCUREMENT) Definitions § 98.900 Adequate evidence. Adequate evidence means information sufficient to support the reasonable belief that a...

  11. INTERMAP: background, aims, design, methods, and descriptive statistics (nondietary).

    PubMed

    Stamler, J; Elliott, P; Dennis, B; Dyer, A R; Kesteloot, H; Liu, K; Ueshima, H; Zhou, B F

    2003-09-01

    Blood pressure (BP) above optimal (< or =120/< or =80 mmHg) is established as a major cardiovascular disease (CVD) risk factor. Prevalence of adverse BP is high in most adult populations; until recently research has been sparse on reasons for this. Since the 1980s, epidemiologic studies confirmed that salt, alcohol intake, and body mass relate directly to BP; dietary potassium, inversely. Several other nutrients also probably influence BP. The DASH feeding trials demonstrated that with the multiple modifications in the DASH combination diet, SBP/DBP (SBP: systolic blood pressure, DBP: diastolic blood pressure) was sizably reduced, independent of calorie balance, alcohol intake, and BP reduction with decreased dietary salt. A key challenge for research is to elucidate specific nutrients accounting for this effect. The general aim of the study was to clarify influences of multiple nutrients on SBP/DBP of individuals over and above effects of Na, K, alcohol, and body mass. Specific aims were, in a cross-sectional epidemiologic study of 4680 men and women aged 40-59 years from 17 diverse population samples in China, Japan, UK, and USA, test 10 prior hypotheses on relations of macronutrients to SBP/DBP and on role of dietary factors in inverse associations of education with BP; test four related subgroup hypotheses; explore associations with SBP/DBP of multiple other nutrients, urinary metabolites, and foods. For these purposes, for all 4680 participants, with standardized high-quality methods, assess individual intake of 76 nutrients from four 24-h dietary recalls/person; measure in two timed 24-h urine collections/person 24-h excretion of Na, K, Ca, Mg, creatinine, amino acids; microalbuminuria; multiple nutrients and metabolites by nuclear magnetic resonance and high-pressure liquid chromatography. Based on eight SBP/DBP measurements/person, and data on multiple possible confounders, utilize mainly multiple linear regression and quantile analyses to test prior

  12. Using the Bootstrap Method for a Statistical Significance Test of Differences between Summary Histograms

    NASA Technical Reports Server (NTRS)

    Xu, Kuan-Man

    2006-01-01

    A new method is proposed to compare statistical differences between summary histograms, which are the histograms summed over a large ensemble of individual histograms. It consists of choosing a distance statistic for measuring the difference between summary histograms and using a bootstrap procedure to calculate the statistical significance level. Bootstrapping is an approach to statistical inference that makes few assumptions about the underlying probability distribution that describes the data. Three distance statistics are compared in this study. They are the Euclidean distance, the Jeffries-Matusita distance and the Kuiper distance. The data used in testing the bootstrap method are satellite measurements of cloud systems called cloud objects. Each cloud object is defined as a contiguous region/patch composed of individual footprints or fields of view. A histogram of measured values over footprints is generated for each parameter of each cloud object and then summary histograms are accumulated over all individual histograms in a given cloud-object size category. The results of statistical hypothesis tests using all three distances as test statistics are generally similar, indicating the validity of the proposed method. The Euclidean distance is determined to be most suitable after comparing the statistical tests of several parameters with distinct probability distributions among three cloud-object size categories. Impacts on the statistical significance levels resulting from differences in the total lengths of satellite footprint data between two size categories are also discussed.

  13. A Statistical Method of Evaluating the Pronunciation Proficiency/Intelligibility of English Presentations by Japanese Speakers

    ERIC Educational Resources Information Center

    Kibishi, Hiroshi; Hirabayashi, Kuniaki; Nakagawa, Seiichi

    2015-01-01

    In this paper, we propose a statistical evaluation method of pronunciation proficiency and intelligibility for presentations made in English by native Japanese speakers. We statistically analyzed the actual utterances of speakers to find combinations of acoustic and linguistic features with high correlation between the scores estimated by the…

  14. Strategies for Enhancing the Learning of Ecological Research Methods and Statistics by Tertiary Environmental Science Students

    ERIC Educational Resources Information Center

    Panizzon, D. L.; Boulton, A. J.

    2004-01-01

    To undertake rigorous research in biology and ecology, students must be able to pose testable hypotheses, design decisive studies, and analyse results using suitable statistics. Yet, few biology students excel in topics involving statistics and most attempt to evade optional courses in research methods. Over the last few years, we have developed…

  15. Statistical method for determining and comparing limits of detection of bioassays.

    PubMed

    Holstein, Carly A; Griffin, Maryclare; Hong, Jing; Sampson, Paul D

    2015-10-01

    The current bioassay development literature lacks the use of statistically robust methods for calculating the limit of detection of a given assay. Instead, researchers often employ simple methods that provide a rough estimate of the limit of detection, often without a measure of the confidence in the estimate. This scarcity of robust methods is likely due to a realistic preference for simple and accessible methods and to a lack of such methods that have reduced the concepts of limit of detection theory to practice for the specific application of bioassays. Here, we have developed a method for determining limits of detection for bioassays that is statistically robust and reduced to practice in a clear and accessible manner geared at researchers, not statisticians. This method utilizes a four-parameter logistic curve fit to translate signal intensity to analyte concentration, which is a curve that is commonly employed in quantitative bioassays. This method generates a 95% confidence interval of the limit of detection estimate to provide a measure of uncertainty and a means by which to compare the analytical sensitivities of different assays statistically. We have demonstrated this method using real data from the development of a paper-based influenza assay in our laboratory to illustrate the steps and features of the method. Using this method, assay developers can calculate statistically valid limits of detection and compare these values for different assays to determine when a change to the assay design results in a statistically significant improvement in analytical sensitivity. PMID:26376354

  16. Physics-based statistical model and simulation method of RF propagation in urban environments

    DOEpatents

    Pao, Hsueh-Yuan; Dvorak, Steven L.

    2010-09-14

    A physics-based statistical model and simulation/modeling method and system of electromagnetic wave propagation (wireless communication) in urban environments. In particular, the model is a computationally efficient close-formed parametric model of RF propagation in an urban environment which is extracted from a physics-based statistical wireless channel simulation method and system. The simulation divides the complex urban environment into a network of interconnected urban canyon waveguides which can be analyzed individually; calculates spectral coefficients of modal fields in the waveguides excited by the propagation using a database of statistical impedance boundary conditions which incorporates the complexity of building walls in the propagation model; determines statistical parameters of the calculated modal fields; and determines a parametric propagation model based on the statistical parameters of the calculated modal fields from which predictions of communications capability may be made.

  17. A Comparative Study of Normalization Methods Used in Statistical Analysis of Oligonucleotide Microarray Data

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Normalization methods used in the statistical analysis of oligonucleotide microarray data were evaluated. The oligonucleotide microarray is considered an efficient analytical tool for analyzing thousands of genes simultaneously in a single experiment. However, systematic variation in microarray, ori...

  18. Modern statistical methods for handling missing repeated measurements in obesity trial data: beyond LOCF.

    PubMed

    Gadbury, G L; Coffey, C S; Allison, D B

    2003-08-01

    This paper brings together some modern statistical methods to address the problem of missing data in obesity trials with repeated measurements. Such missing data occur when subjects miss one or more follow-up visits, or drop out early from an obesity trial. A common approach to dealing with missing data because of dropout is 'last observation carried forward' (LOCF). This method, although intuitively appealing, requires restrictive assumptions to produce valid statistical conclusions. We review the need for obesity trials, the assumptions that must be made regarding missing data in such trials, and some modern statistical methods for analysing data containing missing repeated measurements. These modern methods have fewer limitations and less restrictive assumptions than required for LOCF. Moreover, their recent introduction into current releases of statistical software and textbooks makes them more readily available to the applied data analyses. PMID:12916818

  19. Recommended methods for statistical analysis of data containing less-than-detectable measurements

    SciTech Connect

    Atwood, C.L.; Blackwood, L.G.; Harris, G.A.; Loehr, C.A.

    1990-09-01

    This report is a manual for statistical workers dealing with environmental measurements, when some of the measurements are not given exactly but are only reported as less than detectable. For some statistical settings with such data, many methods have been proposed in the literature, while for others few or none have been proposed. This report gives a recommended method in each of the settings considered. The body of the report gives a brief description of each recommended method. Appendix A gives example programs using the statistical package SAS, for those methods that involve nonstandard methods. Appendix B presents the methods that were compared and the reasons for selecting each recommended method, and explains any fine points that might be of interest. This is an interim version. Future revisions will complete the recommendations. 34 refs., 2 figs., 11 tabs.

  20. Recommended methods for statistical analysis of data containing less-than-detectable measurements

    SciTech Connect

    Atwood, C.L.; Blackwood, L.G.; Harris, G.A.; Loehr, C.A.

    1991-09-01

    This report is a manual for statistical workers dealing with environmental measurements, when some of the measurements are not given exactly but are only reported as less than detectable. For some statistical settings with such data, many methods have been proposed in the literature, while for others few or none have been proposed. This report gives a recommended method in each of the settings considered. The body of the report gives a brief description of each recommended method. Appendix A gives example programs using the statistical package SAS, for those methods that involve nonstandard methods. Appendix B presents the methods that were compared and the reasons for selecting each recommended method, and explains any fine points that might be of interest. 7 refs., 4 figs.

  1. An improved method for statistical analysis of raw accelerator mass spectrometry data

    SciTech Connect

    Gutjahr, A.; Phillips, F.; Kubik, P.W.; Elmore, D.

    1987-01-01

    Hierarchical statistical analysis is an appropriate method for statistical treatment of raw accelerator mass spectrometry (AMS) data. Using Monte Carlo simulations we show that this method yields more accurate estimates of isotope ratios and analytical uncertainty than the generally used propagation of errors approach. The hierarchical analysis is also useful in design of experiments because it can be used to identify sources of variability. 8 refs., 2 figs.

  2. Probability of identification: a statistical model for the validation of qualitative botanical identification methods.

    PubMed

    LaBudde, Robert A; Harnly, James M

    2012-01-01

    A qualitative botanical identification method (BIM) is an analytical procedure that returns a binary result (1 = Identified, 0 = Not Identified). A BIM may be used by a buyer, manufacturer, or regulator to determine whether a botanical material being tested is the same as the target (desired) material, or whether it contains excessive nontarget (undesirable) material. The report describes the development and validation of studies for a BIM based on the proportion of replicates identified, or probability of identification (POI), as the basic observed statistic. The statistical procedures proposed for data analysis follow closely those of the probability of detection, and harmonize the statistical concepts and parameters between quantitative and qualitative method validation. Use of POI statistics also harmonizes statistical concepts for botanical, microbiological, toxin, and other analyte identification methods that produce binary results. The POI statistical model provides a tool for graphical representation of response curves for qualitative methods, reporting of descriptive statistics, and application of performance requirements. Single collaborator and multicollaborative study examples are given. PMID:22468371

  3. A new statistical precipitation downscaling method with Bayesian model averaging: a case study in China

    NASA Astrophysics Data System (ADS)

    Zhang, Xianliang; Yan, Xiaodong

    2015-11-01

    A new statistical downscaling method was developed and applied to downscale monthly total precipitation from 583 stations in China. Generally, there are two steps involved in statistical downscaling: first, the predictors are selected (large-scale variables) and transformed; and second, a model between the predictors and the predictand (in this case, precipitation) is established. In the first step, a selection process of the predictor domain, called the optimum correlation method (OCM), was developed to transform the predictors. The transformed series obtained by the OCM showed much better correlation with the predictand than those obtained by the traditional transform method for the same predictor. Moreover, the method combining OCM and linear regression obtained better downscaling results than the traditional linear regression method, suggesting that the OCM could be used to improve the results of statistical downscaling. In the second step, Bayesian model averaging (BMA) was adopted as an alternative to linear regression. The method combining the OCM and BMA showed much better performance than the method combining the OCM and linear regression. Thus, BMA could be used as an alternative to linear regression in the second step of statistical downscaling. In conclusion, the downscaling method combining OCM and BMA produces more accurate results than the multiple linear regression method when used to statistically downscale large-scale variables.

  4. Development and Evaluation of a Hybrid Dynamical-Statistical Downscaling Method

    NASA Astrophysics Data System (ADS)

    Walton, Daniel Burton

    Regional climate change studies usually rely on downscaling of global climate model (GCM) output in order to resolve important fine-scale features and processes that govern local climate. Previous efforts have used one of two techniques: (1) dynamical downscaling, in which a regional climate model is forced at the boundaries by GCM output, or (2) statistical downscaling, which employs historical empirical relationships to go from coarse to fine resolution. Studies using these methods have been criticized because they either dynamical downscaled only a few GCMs, or used statistical downscaling on an ensemble of GCMs, but missed important dynamical effects in the climate change signal. This study describes the development and evaluation of a hybrid dynamical-statstical downscaling method that utilizes aspects of both dynamical and statistical downscaling to address these concerns. The first step of the hybrid method is to use dynamical downscaling to understand the most important physical processes that contribute to the climate change signal in the region of interest. Then a statistical model is built based on the patterns and relationships identified from dynamical downscaling. This statistical model can be used to downscale an entire ensemble of GCMs quickly and efficiently. The hybrid method is first applied to a domain covering Los Angeles Region to generate projections of temperature change between the 2041-2060 and 1981-2000 periods for 32 CMIP5 GCMs. The hybrid method is also applied to a larger region covering all of California and the adjacent ocean. The hybrid method works well in both areas, primarily because a single feature, the land-sea contrast in the warming, controls the overwhelming majority of the spatial detail. Finally, the dynamically downscaled temperature change patterns are compared to those produced by two commonly-used statistical methods, BCSD and BCCA. Results show that dynamical downscaling recovers important spatial features that the

  5. Teaching Research Methods and Statistics in eLearning Environments: Pedagogy, Practical Examples, and Possible Futures.

    PubMed

    Rock, Adam J; Coventry, William L; Morgan, Methuen I; Loi, Natasha M

    2016-01-01

    Generally, academic psychologists are mindful of the fact that, for many students, the study of research methods and statistics is anxiety provoking (Gal et al., 1997). Given the ubiquitous and distributed nature of eLearning systems (Nof et al., 2015), teachers of research methods and statistics need to cultivate an understanding of how to effectively use eLearning tools to inspire psychology students to learn. Consequently, the aim of the present paper is to discuss critically how using eLearning systems might engage psychology students in research methods and statistics. First, we critically appraise definitions of eLearning. Second, we examine numerous important pedagogical principles associated with effectively teaching research methods and statistics using eLearning systems. Subsequently, we provide practical examples of our own eLearning-based class activities designed to engage psychology students to learn statistical concepts such as Factor Analysis and Discriminant Function Analysis. Finally, we discuss general trends in eLearning and possible futures that are pertinent to teachers of research methods and statistics in psychology. PMID:27014147

  6. Teaching Research Methods and Statistics in eLearning Environments: Pedagogy, Practical Examples, and Possible Futures

    PubMed Central

    Rock, Adam J.; Coventry, William L.; Morgan, Methuen I.; Loi, Natasha M.

    2016-01-01

    Generally, academic psychologists are mindful of the fact that, for many students, the study of research methods and statistics is anxiety provoking (Gal et al., 1997). Given the ubiquitous and distributed nature of eLearning systems (Nof et al., 2015), teachers of research methods and statistics need to cultivate an understanding of how to effectively use eLearning tools to inspire psychology students to learn. Consequently, the aim of the present paper is to discuss critically how using eLearning systems might engage psychology students in research methods and statistics. First, we critically appraise definitions of eLearning. Second, we examine numerous important pedagogical principles associated with effectively teaching research methods and statistics using eLearning systems. Subsequently, we provide practical examples of our own eLearning-based class activities designed to engage psychology students to learn statistical concepts such as Factor Analysis and Discriminant Function Analysis. Finally, we discuss general trends in eLearning and possible futures that are pertinent to teachers of research methods and statistics in psychology. PMID:27014147

  7. Which Ab Initio Wave Function Methods Are Adequate for Quantitative Calculations of the Energies of Biradicals? The Performance of Coupled-Cluster and Multi-Reference Methods Along a Single-Bond Dissociation Coordinate

    SciTech Connect

    Yang, Ke; Jalan, Amrit; Green, William H.; Truhlar, Donald G.

    2013-01-08

    We examine the accuracy of single-reference and multireference correlated wave function methods for predicting accurate energies and potential energy curves of biradicals. The biradicals considered are intermediate species along the bond dissociation coordinates for breaking the F-F bond in F2, the O-O bond in H2O2, and the C-C bond in CH3CH3. We apply a host of single-reference and multireference approximations in a consistent way to the same cases to provide a better assessment of their relative accuracies than was previously possible. The most accurate method studied is coupled cluster theory with all connected excitations through quadruples, CCSDTQ. Without explicit quadruple excitations, the most accurate potential energy curves are obtained by the single-reference RCCSDt method, followed, in order of decreasing accuracy, by UCCSDT, RCCSDT, UCCSDt, seven multireference methods, including perturbation theory, configuration interaction, and coupled-cluster methods (with MRCI+Q being the best and Mk-MR-CCSD the least accurate), four CCSD(T) methods, and then CCSD.

  8. Inter-comparison of statistical downscaling methods for projection of extreme precipitation in Europe

    NASA Astrophysics Data System (ADS)

    Sunyer, M. A.; Hundecha, Y.; Lawrence, D.; Madsen, H.; Willems, P.; Martinkova, M.; Vormoor, K.; Bürger, G.; Hanel, M.; Kriaučiūnienė, J.; Loukas, A.; Osuch, M.; Yücel, I.

    2014-06-01

    Information on extreme precipitation for future climate is needed to assess the changes in the frequency and intensity of flooding. The primary source of information in climate change impact studies is climate model projections. However, due to the coarse resolution and biases of these models, they cannot be directly used in hydrological models. Hence, statistical downscaling is necessary to address climate change impacts at the catchment scale. This study compares eight statistical downscaling methods often used in climate change impact studies. Four methods are based on change factors, three are bias correction methods, and one is a perfect prognosis method. The eight methods are used to downscale precipitation output from fifteen regional climate models (RCMs) from the ENSEMBLES project for eleven catchments in Europe. The overall results point to an increase in extreme precipitation in most catchments in both winter and summer. For individual catchments, the downscaled time series tend to agree on the direction of the change but differ in the magnitude. Differences between the statistical downscaling methods vary between the catchments and depend on the season analysed. Similarly, general conclusions cannot be drawn regarding the differences between change factor and bias correction methods. The performance of the bias correction methods during the control period also depends on the catchment, but in most cases they represent an improvement compared to RCM outputs. Analysis of the variance in the ensemble of RCMs and statistical downscaling methods indicates that up to half of the total variance is derived from the statistical downscaling methods. This study illustrates the large variability in the expected changes in extreme precipitation and highlights the need of considering an ensemble of both statistical downscaling methods and climate models.

  9. Initial evaluation of Centroidal Voronoi Tessellation method for statistical sampling and function integration.

    SciTech Connect

    Romero, Vicente Jose; Peterson, Janet S.; Burkhardt, John V.; Gunzburger, Max Donald

    2003-09-01

    A recently developed Centroidal Voronoi Tessellation (CVT) unstructured sampling method is investigated here to assess its suitability for use in statistical sampling and function integration. CVT efficiently generates a highly uniform distribution of sample points over arbitrarily shaped M-Dimensional parameter spaces. It has recently been shown on several 2-D test problems to provide superior point distributions for generating locally conforming response surfaces. In this paper, its performance as a statistical sampling and function integration method is compared to that of Latin-Hypercube Sampling (LHS) and Simple Random Sampling (SRS) Monte Carlo methods, and Halton and Hammersley quasi-Monte-Carlo sequence methods. Specifically, sampling efficiencies are compared for function integration and for resolving various statistics of response in a 2-D test problem. It is found that on balance CVT performs best of all these sampling methods on our test problems.

  10. 34 CFR 85.900 - Adequate evidence.

    Code of Federal Regulations, 2010 CFR

    2010-07-01

    ...) Definitions § 85.900 Adequate evidence. Adequate evidence means information sufficient to support the reasonable belief that a particular act or omission has occurred. Authority: E.O. 12549 (3 CFR, 1986 Comp., p. 189); E.O 12689 (3 CFR, 1989 Comp., p. 235); 20 U.S.C. 1082, 1094, 1221e-3 and 3474; and Sec....

  11. 29 CFR 452.110 - Adequate safeguards.

    Code of Federal Regulations, 2010 CFR

    2010-07-01

    ... 29 Labor 2 2010-07-01 2010-07-01 false Adequate safeguards. 452.110 Section 452.110 Labor... DISCLOSURE ACT OF 1959 Election Procedures; Rights of Members § 452.110 Adequate safeguards. (a) In addition to the election safeguards discussed in this part, the Act contains a general mandate in section...

  12. 29 CFR 452.110 - Adequate safeguards.

    Code of Federal Regulations, 2011 CFR

    2011-07-01

    ... 29 Labor 2 2011-07-01 2011-07-01 false Adequate safeguards. 452.110 Section 452.110 Labor... DISCLOSURE ACT OF 1959 Election Procedures; Rights of Members § 452.110 Adequate safeguards. (a) In addition to the election safeguards discussed in this part, the Act contains a general mandate in section...

  13. Review of statistical methods used in enhanced-oil-recovery research and performance prediction. [131 references

    SciTech Connect

    Selvidge, J.E.

    1982-06-01

    Recent literature in the field of enhanced oil recovery (EOR) was surveyed to determine the extent to which researchers in EOR take advantage of statistical techniques in analyzing their data. In addition to determining the current level of reliance on statistical tools, another objective of this study is to promote by example the greater use of these tools. To serve this objective, the discussion of the techniques highlights the observed trend toward the use of increasingly more sophisticated methods and points out the strengths and pitfalls of different approaches. Several examples are also given of opportunities for extending EOR research findings by additional statistical manipulation. The search of the EOR literature, conducted mainly through computerized data bases, yielded nearly 200 articles containing mathematical analysis of the research. Of these, 21 were found to include examples of statistical approaches to data analysis and are discussed in detail in this review. The use of statistical techniques, as might be expected from their general purpose nature, extends across nearly all types of EOR research covering thermal methods of recovery, miscible processes, and micellar polymer floods. Data come from field tests, the laboratory, and computer simulation. The statistical methods range from simple comparisons of mean values to multiple non-linear regression equations and to probabilistic decision functions. The methods are applied to both engineering and economic data. The results of the survey are grouped by statistical technique and include brief descriptions of each of the 21 relevant papers. Complete abstracts of the papers are included in the bibliography. Brief bibliographic information (without abstracts) is also given for the articles identified in the initial search as containing mathematical analyses using other than statistical methods.

  14. A Comparative Review of Sensitivity and Uncertainty Analysis of Large-Scale Systems - II: Statistical Methods

    SciTech Connect

    Cacuci, Dan G.; Ionescu-Bujor, Mihaela

    2004-07-15

    Part II of this review paper highlights the salient features of the most popular statistical methods currently used for local and global sensitivity and uncertainty analysis of both large-scale computational models and indirect experimental measurements. These statistical procedures represent sampling-based methods (random sampling, stratified importance sampling, and Latin Hypercube sampling), first- and second-order reliability algorithms (FORM and SORM, respectively), variance-based methods (correlation ratio-based methods, the Fourier Amplitude Sensitivity Test, and the Sobol Method), and screening design methods (classical one-at-a-time experiments, global one-at-a-time design methods, systematic fractional replicate designs, and sequential bifurcation designs). It is emphasized that all statistical uncertainty and sensitivity analysis procedures first commence with the 'uncertainty analysis' stage and only subsequently proceed to the 'sensitivity analysis' stage; this path is the exact reverse of the conceptual path underlying the methods of deterministic sensitivity and uncertainty analysis where the sensitivities are determined prior to using them for uncertainty analysis. By comparison to deterministic methods, statistical methods for uncertainty and sensitivity analysis are relatively easier to develop and use but cannot yield exact values of the local sensitivities. Furthermore, current statistical methods have two major inherent drawbacks as follows: 1. Since many thousands of simulations are needed to obtain reliable results, statistical methods are at best expensive (for small systems) or, at worst, impracticable (e.g., for large time-dependent systems).2. Since the response sensitivities and parameter uncertainties are inherently and inseparably amalgamated in the results produced by these methods, improvements in parameter uncertainties cannot be directly propagated to improve response uncertainties; rather, the entire set of simulations and

  15. RAId_DbS: Method for Peptide ID using Database Search with Accurate Statistics

    NASA Astrophysics Data System (ADS)

    Alves, Gelio; Ogurtsov, Aleksey; Yu, Yi-Kuo

    2007-03-01

    The key to proteomics studies, essential in systems biology, is peptide identification. Under tandem mass spectrometry, each spectrum generated consists of a list of mass/charge peaks along with their intensities. Software analysis is then required to identify from the spectrum peptide candidates that best interpret the spectrum. The library search, which compares the spectral peaks against theoretical peaks generated by each peptide in a library, is among the most popular methods. This method, although robust, lacks good quantitative statistical underpinning. As we show, many library search algorithms suffer from statistical instability. The need for a better statistical basis prompted us to develop RAId_DbS. Taking into account the skewness in the peak intensity distribution while scoring peptides, RAId_DbS provides an accurate statistical significance assignment to each peptide candidate. RAId_DbS will be a valuable tool especially when one intends to identify proteins through peptide identifications.

  16. Feasibility of voxel-based statistical analysis method for myocardial PET

    NASA Astrophysics Data System (ADS)

    Ram Yu, A.; Kim, Jin Su; Paik, Chang H.; Kim, Kyeong Min; Moo Lim, Sang

    2014-09-01

    Although statistical parametric mapping (SPM) analysis is widely used in neuroimaging studies, to our best knowledge, there was no application to myocardial PET data analysis. In this study, we developed the voxel based statistical analysis method for myocardial PET which provides statistical comparison results between groups in image space. PET Emission data of normal and myocardial infarction rats were acquired For the SPM analysis, a rat heart template was created. In addition, individual PET data was spatially normalized and smoothed. Two sample t-tests were performed to identify the myocardial infarct region. This developed SPM method was compared with conventional ROI methods. Myocardial glucose metabolism was decreased in the lateral wall of the left ventricle. In the result of ROI analysis, the mean value of the lateral wall was 29% decreased. The newly developed SPM method for myocardial PET could provide quantitative information in myocardial PET study.

  17. Differential Expression Analysis for RNA-Seq: An Overview of Statistical Methods and Computational Software

    PubMed Central

    Huang, Huei-Chung; Niu, Yi; Qin, Li-Xuan

    2015-01-01

    Deep sequencing has recently emerged as a powerful alternative to microarrays for the high-throughput profiling of gene expression. In order to account for the discrete nature of RNA sequencing data, new statistical methods and computational tools have been developed for the analysis of differential expression to identify genes that are relevant to a disease such as cancer. In this paper, it is thus timely to provide an overview of these analysis methods and tools. For readers with statistical background, we also review the parameter estimation algorithms and hypothesis testing strategies used in these methods. PMID:26688660

  18. Verification of statistical method CORN for modeling of microfuel in the case of high grain concentration

    NASA Astrophysics Data System (ADS)

    Chukbar, B. K.

    2015-12-01

    Two methods of modeling a double-heterogeneity fuel are studied: the deterministic positioning and the statistical method CORN of the MCU software package. The effect of distribution of microfuel in a pebble bed on the calculation results is studied. The results of verification of the statistical method CORN for the cases of the microfuel concentration up to 170 cm-3 in a pebble bed are presented. The admissibility of homogenization of the microfuel coating with the graphite matrix is studied. The dependence of the reactivity on the relative location of fuel and graphite spheres in a pebble bed is found.

  19. Verification of statistical method CORN for modeling of microfuel in the case of high grain concentration

    SciTech Connect

    Chukbar, B. K.

    2015-12-15

    Two methods of modeling a double-heterogeneity fuel are studied: the deterministic positioning and the statistical method CORN of the MCU software package. The effect of distribution of microfuel in a pebble bed on the calculation results is studied. The results of verification of the statistical method CORN for the cases of the microfuel concentration up to 170 cm{sup –3} in a pebble bed are presented. The admissibility of homogenization of the microfuel coating with the graphite matrix is studied. The dependence of the reactivity on the relative location of fuel and graphite spheres in a pebble bed is found.

  20. A NEW METHOD TO CORRECT FOR FIBER COLLISIONS IN GALAXY TWO-POINT STATISTICS

    SciTech Connect

    Guo Hong; Zehavi, Idit; Zheng Zheng

    2012-09-10

    In fiber-fed galaxy redshift surveys, the finite size of the fiber plugs prevents two fibers from being placed too close to one another, limiting the ability to study galaxy clustering on all scales. We present a new method for correcting such fiber collision effects in galaxy clustering statistics based on spectroscopic observations. The target galaxy sample is divided into two distinct populations according to the targeting algorithm of fiber placement, one free of fiber collisions and the other consisting of collided galaxies. The clustering statistics are a combination of the contributions from these two populations. Our method makes use of observations in tile overlap regions to measure the contributions from the collided population, and to therefore recover the full clustering statistics. The method is rooted in solid theoretical ground and is tested extensively on mock galaxy catalogs. We demonstrate that our method can well recover the projected and the full three-dimensional (3D) redshift-space two-point correlation functions (2PCFs) on scales both below and above the fiber collision scale, superior to the commonly used nearest neighbor and angular correction methods. We discuss potential systematic effects in our method. The statistical correction accuracy of our method is only limited by sample variance, which scales down with (the square root of) the volume probed. For a sample similar to the final SDSS-III BOSS galaxy sample, the statistical correction error is expected to be at the level of 1% on scales {approx}0.1-30 h {sup -1} Mpc for the 2PCFs. The systematic error only occurs on small scales, caused by imperfect correction of collision multiplets, and its magnitude is expected to be smaller than 5%. Our correction method, which can be generalized to other clustering statistics as well, enables more accurate measurements of full 3D galaxy clustering on all scales with galaxy redshift surveys.

  1. The Effectiveness of Propositional Manipulation as a Lecturing Method in the Statistics Knowledge Domain

    ERIC Educational Resources Information Center

    Leppink, Jimmie; Broers, Nick J.; Imbos, Tjaart; van der Vleuten, Cees P. M.; Berger, Martijn P. F.

    2013-01-01

    The current experiment examined the potential effects of the method of propositional manipulation (MPM) as a lecturing method on motivation to learn and conceptual understanding of statistics. MPM aims to help students develop conceptual understanding by guiding them into self-explanation at two different stages: First, at the stage of…

  2. Fine Mapping Causal Variants with an Approximate Bayesian Method Using Marginal Test Statistics.

    PubMed

    Chen, Wenan; Larrabee, Beth R; Ovsyannikova, Inna G; Kennedy, Richard B; Haralambieva, Iana H; Poland, Gregory A; Schaid, Daniel J

    2015-07-01

    Two recently developed fine-mapping methods, CAVIAR and PAINTOR, demonstrate better performance over other fine-mapping methods. They also have the advantage of using only the marginal test statistics and the correlation among SNPs. Both methods leverage the fact that the marginal test statistics asymptotically follow a multivariate normal distribution and are likelihood based. However, their relationship with Bayesian fine mapping, such as BIMBAM, is not clear. In this study, we first show that CAVIAR and BIMBAM are actually approximately equivalent to each other. This leads to a fine-mapping method using marginal test statistics in the Bayesian framework, which we call CAVIAR Bayes factor (CAVIARBF). Another advantage of the Bayesian framework is that it can answer both association and fine-mapping questions. We also used simulations to compare CAVIARBF with other methods under different numbers of causal variants. The results showed that both CAVIARBF and BIMBAM have better performance than PAINTOR and other methods. Compared to BIMBAM, CAVIARBF has the advantage of using only marginal test statistics and takes about one-quarter to one-fifth of the running time. We applied different methods on two independent cohorts of the same phenotype. Results showed that CAVIARBF, BIMBAM, and PAINTOR selected the same top 3 SNPs; however, CAVIARBF and BIMBAM had better consistency in selecting the top 10 ranked SNPs between the two cohorts. Software is available at https://bitbucket.org/Wenan/caviarbf. PMID:25948564

  3. Americans Getting Adequate Water Daily, CDC Finds

    MedlinePlus

    ... medlineplus/news/fullstory_158510.html Americans Getting Adequate Water Daily, CDC Finds Men take in an average ... new government report finds most are getting enough water each day. The data, from the U.S. National ...

  4. Americans Getting Adequate Water Daily, CDC Finds

    MedlinePlus

    ... gov/news/fullstory_158510.html Americans Getting Adequate Water Daily, CDC Finds Men take in an average ... new government report finds most are getting enough water each day. The data, from the U.S. National ...

  5. A method for determining the weak statistical stationarity of a random process

    NASA Technical Reports Server (NTRS)

    Sadeh, W. Z.; Koper, C. A., Jr.

    1978-01-01

    A method for determining the weak statistical stationarity of a random process is presented. The core of this testing procedure consists of generating an equivalent ensemble which approximates a true ensemble. Formation of an equivalent ensemble is accomplished through segmenting a sufficiently long time history of a random process into equal, finite, and statistically independent sample records. The weak statistical stationarity is ascertained based on the time invariance of the equivalent-ensemble averages. Comparison of these averages with their corresponding time averages over a single sample record leads to a heuristic estimate of the ergodicity of a random process. Specific variance tests are introduced for evaluating the statistical independence of the sample records, the time invariance of the equivalent-ensemble autocorrelations, and the ergodicity. Examination and substantiation of these procedures were conducted utilizing turbulent velocity signals.

  6. Impact of Statistical Learning Methods on the Predictive Power of Multivariate Normal Tissue Complication Probability Models

    SciTech Connect

    Xu Chengjian; Schaaf, Arjen van der; Schilstra, Cornelis; Langendijk, Johannes A.; Veld, Aart A. van't

    2012-03-15

    Purpose: To study the impact of different statistical learning methods on the prediction performance of multivariate normal tissue complication probability (NTCP) models. Methods and Materials: In this study, three learning methods, stepwise selection, least absolute shrinkage and selection operator (LASSO), and Bayesian model averaging (BMA), were used to build NTCP models of xerostomia following radiotherapy treatment for head and neck cancer. Performance of each learning method was evaluated by a repeated cross-validation scheme in order to obtain a fair comparison among methods. Results: It was found that the LASSO and BMA methods produced models with significantly better predictive power than that of the stepwise selection method. Furthermore, the LASSO method yields an easily interpretable model as the stepwise method does, in contrast to the less intuitive BMA method. Conclusions: The commonly used stepwise selection method, which is simple to execute, may be insufficient for NTCP modeling. The LASSO method is recommended.

  7. A model and variance reduction method for computing statistical outputs of stochastic elliptic partial differential equations

    SciTech Connect

    Vidal-Codina, F.; Nguyen, N.C.; Giles, M.B.; Peraire, J.

    2015-09-15

    We present a model and variance reduction method for the fast and reliable computation of statistical outputs of stochastic elliptic partial differential equations. Our method consists of three main ingredients: (1) the hybridizable discontinuous Galerkin (HDG) discretization of elliptic partial differential equations (PDEs), which allows us to obtain high-order accurate solutions of the governing PDE; (2) the reduced basis method for a new HDG discretization of the underlying PDE to enable real-time solution of the parameterized PDE in the presence of stochastic parameters; and (3) a multilevel variance reduction method that exploits the statistical correlation among the different reduced basis approximations and the high-fidelity HDG discretization to accelerate the convergence of the Monte Carlo simulations. The multilevel variance reduction method provides efficient computation of the statistical outputs by shifting most of the computational burden from the high-fidelity HDG approximation to the reduced basis approximations. Furthermore, we develop a posteriori error estimates for our approximations of the statistical outputs. Based on these error estimates, we propose an algorithm for optimally choosing both the dimensions of the reduced basis approximations and the sizes of Monte Carlo samples to achieve a given error tolerance. We provide numerical examples to demonstrate the performance of the proposed method.

  8. Multi-Reader ROC studies with Split-Plot Designs: A Comparison of Statistical Methods

    PubMed Central

    Obuchowski, Nancy A.; Gallas, Brandon D.; Hillis, Stephen L.

    2012-01-01

    Rationale and Objectives Multi-reader imaging trials often use a factorial design, where study patients undergo testing with all imaging modalities and readers interpret the results of all tests for all patients. A drawback of the design is the large number of interpretations required of each reader. Split-plot designs have been proposed as an alternative, in which one or a subset of readers interprets all images of a sample of patients, while other readers interpret the images of other samples of patients. In this paper we compare three methods of analysis for the split-plot design. Materials and Methods Three statistical methods are presented: Obuchowski-Rockette method modified for the split-plot design, a newly proposed marginal-mean ANOVA approach, and an extension of the three-sample U-statistic method. A simulation study using the Roe-Metz model was performed to compare the type I error rate, power and confidence interval coverage of the three test statistics. Results The type I error rates for all three methods are close to the nominal level but tend to be slightly conservative. The statistical power is nearly identical for the three methods. The coverage of 95% CIs fall close to the nominal coverage for small and large sample sizes. Conclusions The split-plot MRMC study design can be statistically efficient compared with the factorial design, reducing the number of interpretations required per reader. Three methods of analysis, shown to have nominal type I error rate, similar power, and nominal CI coverage, are available for this study design. PMID:23122570

  9. Assessment of methods for creating a national building statistics database for atmospheric dispersion modeling

    SciTech Connect

    Velugubantla, S. P.; Burian, S. J.; Brown, M. J.; McKinnon, A. T.; McPherson, T. N.; Han, W. S.

    2004-01-01

    Mesoscale meteorological codes and transport and dispersion models are increasingly being applied in urban areas. Representing urban terrain characteristics in these models is critical for accurate predictions of air flow, heating and cooling, and airborne contaminant concentrations in cities. A key component of urban terrain characterization is the description of building morphology (e.g., height, plan area, frontal area) and derived properties (e.g., roughness length). Methods to determine building morphological statistics range from manual field surveys to automated processing of digital building databases. In order to improve the quality and consistency of mesoscale meteorological and atmospheric dispersion modeling, a national dataset of building morphological statistics is needed. Currently, due to the expense and logistics of conducting detailed field surveys, building statistics have been derived for only small sections of a few cities. In most other cities, modeling projects rely on building statistics estimated using intuition and best guesses. There has been increasing emphasis in recent years to derive building statistics using digital building data or other data sources as a proxy for those data. Although there is a current expansion in public and private sector development of digital building data, at present there is insufficient data to derive a national building statistics database using automated analysis tools. Too many cities lack digital data on building footprints and heights and many of the cities having such data do so for only small areas. Due to the lack of sufficient digital building data, other datasets are used to estimate building statistics. Land use often serves as means to provide building statistics for a model domain, but the strength and consistency of the relationship between land use and building morphology is largely uncertain. In this paper, we investigate whether building statistics can be correlated to the underlying land

  10. Model averaging methods to merge operational statistical and dynamic seasonal streamflow forecasts in Australia

    NASA Astrophysics Data System (ADS)

    Schepen, Andrew; Wang, Q. J.

    2015-03-01

    The Australian Bureau of Meteorology produces statistical and dynamic seasonal streamflow forecasts. The statistical and dynamic forecasts are similarly reliable in ensemble spread; however, skill varies by catchment and season. Therefore, it may be possible to optimize forecasting skill by weighting and merging statistical and dynamic forecasts. Two model averaging methods are evaluated for merging forecasts for 12 locations. The first method, Bayesian model averaging (BMA), applies averaging to forecast probability densities (and thus cumulative probabilities) for a given forecast variable value. The second method, quantile model averaging (QMA), applies averaging to forecast variable values (quantiles) for a given cumulative probability (quantile fraction). BMA and QMA are found to perform similarly in terms of overall skill scores and reliability in ensemble spread. Both methods improve forecast skill across catchments and seasons. However, when both the statistical and dynamical forecasting approaches are skillful but produce, on special occasions, very different event forecasts, the BMA merged forecasts for these events can have unusually wide and bimodal distributions. In contrast, the distributions of the QMA merged forecasts for these events are narrower, unimodal and generally more smoothly shaped, and are potentially more easily communicated to and interpreted by the forecast users. Such special occasions are found to be rare. However, every forecast counts in an operational service, and therefore the occasional contrast in merged forecasts between the two methods may be more significant than the indifference shown by the overall skill and reliability performance.

  11. A Comparison of Statistical Methods for the Discovery of Genetic Risk Factors Using Longitudinal Family Study Designs

    PubMed Central

    Burkett, Kelly M.; Roy-Gagnon, Marie-Hélène; Lefebvre, Jean-François; Wang, Cheng; Fontaine-Bisson, Bénédicte; Dubois, Lise

    2015-01-01

    The etiology of immune-related diseases or traits is often complex, involving many genetic and environmental factors and their interactions. While methodological approaches focusing on an outcome measured at one time point have succeeded in identifying genetic factors involved in immune-related traits, they fail to capture complex disease mechanisms that fluctuate over time. It is increasingly recognized that longitudinal studies, where an outcome is measured at multiple time points, have great potential to shed light on complex disease mechanisms involving genetic factors. However, longitudinal data require specialized statistical methods, especially in family studies where multiple sources of correlation in the data must be modeled. Using simulated data with known genetic effects, we examined the performance of different analytical methods for investigating associations between genetic factors and longitudinal phenotypes in twin data. The simulations were modeled on data from the Québec Newborn Twin Study, an ongoing population-based longitudinal study of twin births with multiple phenotypes, such as cortisol levels and body mass index, collected multiple times in infancy and early childhood and with sequencing data on immune-related genes and pathways. We compared approaches that we classify as (1) family-based methods applied to summaries of the observations over time, (2) longitudinal-based methods with simplifications of the familial correlation, and (3) Bayesian family-based method with simplifications of the temporal correlation. We found that for estimation of the genetic main and interaction effects, all methods gave estimates close to the true values and had similar power. If heritability estimation is desired, approaches of type (1) also provide heritability estimates close to the true value. Our work shows that the simpler approaches are likely adequate to detect genetic effects; however, interpretation of these effects is more challenging. PMID

  12. A study of two statistical methods as applied to shuttle solid rocket booster expenditures

    NASA Technical Reports Server (NTRS)

    Perlmutter, M.; Huang, Y.; Graves, M.

    1974-01-01

    The state probability technique and the Monte Carlo technique are applied to finding shuttle solid rocket booster expenditure statistics. For a given attrition rate per launch, the probable number of boosters needed for a given mission of 440 launches is calculated. Several cases are considered, including the elimination of the booster after a maximum of 20 consecutive launches. Also considered is the case where the booster is composed of replaceable components with independent attrition rates. A simple cost analysis is carried out to indicate the number of boosters to build initially, depending on booster costs. Two statistical methods were applied in the analysis: (1) state probability method which consists of defining an appropriate state space for the outcome of the random trials, and (2) model simulation method or the Monte Carlo technique. It was found that the model simulation method was easier to formulate while the state probability method required less computing time and was more accurate.

  13. An automatic abrupt information extraction method based on singular value decomposition and higher-order statistics

    NASA Astrophysics Data System (ADS)

    He, Tian; Ye, Wu; Pan, Qiang; Liu, Xiandong

    2016-02-01

    One key aspect of local fault diagnosis is how to effectively extract abrupt features from the vibration signals. This paper proposes a method to automatically extract abrupt information based on singular value decomposition and higher-order statistics. In order to observe the distribution law of singular values, a numerical analysis to simulate the noise, periodic signal, abrupt signal and singular value distribution is conducted. Based on higher-order statistics and spectrum analysis, a method to automatically choose the upper and lower borders of the singular value interval reflecting the abrupt information is built. And the selected singular values derived from this method are used to reconstruct abrupt signals. It is proven that the method is able to obtain accurate results by processing the rub-impact fault signal measured from the experiments. The analytical and experimental results indicate that the proposed method is feasible for automatically extracting abrupt information caused by faults like the rotor-stator rub-impact.

  14. Statistical Physics Methods Provide the Exact Solution to a Long-Standing Problem of Genetics

    NASA Astrophysics Data System (ADS)

    Samal, Areejit; Martin, Olivier C.

    2015-06-01

    Analytic and computational methods developed within statistical physics have found applications in numerous disciplines. In this Letter, we use such methods to solve a long-standing problem in statistical genetics. The problem, posed by Haldane and Waddington [Genetics 16, 357 (1931)], concerns so-called recombinant inbred lines (RILs) produced by repeated inbreeding. Haldane and Waddington derived the probabilities of RILs when considering two and three genes but the case of four or more genes has remained elusive. Our solution uses two probabilistic frameworks relatively unknown outside of physics: Glauber's formula and self-consistent equations of the Schwinger-Dyson type. Surprisingly, this combination of statistical formalisms unveils the exact probabilities of RILs for any number of genes. Extensions of the framework may have applications in population genetics and beyond.

  15. Neural network approaches versus statistical methods in classification of multisource remote sensing data

    NASA Technical Reports Server (NTRS)

    Benediktsson, Jon A.; Swain, Philip H.; Ersoy, Okan K.

    1990-01-01

    Neural network learning procedures and statistical classificaiton methods are applied and compared empirically in classification of multisource remote sensing and geographic data. Statistical multisource classification by means of a method based on Bayesian classification theory is also investigated and modified. The modifications permit control of the influence of the data sources involved in the classification process. Reliability measures are introduced to rank the quality of the data sources. The data sources are then weighted according to these rankings in the statistical multisource classification. Four data sources are used in experiments: Landsat MSS data and three forms of topographic data (elevation, slope, and aspect). Experimental results show that two different approaches have unique advantages and disadvantages in this classification application.

  16. A similarity retrieval method for functional magnetic resonance imaging (fMRI) statistical maps

    NASA Astrophysics Data System (ADS)

    Tungaraza, R. F.; Guan, J.; Rolfe, S.; Atmosukarto, I.; Poliakov, A.; Kleinhans, N. M.; Aylward, E.; Ojemann, J.; Brinkley, J. F.; Shapiro, L. G.

    2009-02-01

    We propose a method for retrieving similar fMRI statistical images given a query fMRI statistical image. Our method thresholds the voxels within those images and extracts spatially distinct regions from the voxels that remain. Each region is defined by a feature vector that contains the region centroid, the region area, the average activation value for all the voxels within that region, the variance of those activation values, the average distance of each voxel within that region to the region's centroid, and the variance of the voxel's distance to the region's centroid. The similarity between two images is obtained by the summed minimum distance of their constituent feature vectors. Results on a dataset of fMRI statistical images from experiments involving distinct cognitive tasks are shown.

  17. Statistical Physics Methods Provide the Exact Solution to a Long-Standing Problem of Genetics.

    PubMed

    Samal, Areejit; Martin, Olivier C

    2015-06-12

    Analytic and computational methods developed within statistical physics have found applications in numerous disciplines. In this Letter, we use such methods to solve a long-standing problem in statistical genetics. The problem, posed by Haldane and Waddington [Genetics 16, 357 (1931)], concerns so-called recombinant inbred lines (RILs) produced by repeated inbreeding. Haldane and Waddington derived the probabilities of RILs when considering two and three genes but the case of four or more genes has remained elusive. Our solution uses two probabilistic frameworks relatively unknown outside of physics: Glauber's formula and self-consistent equations of the Schwinger-Dyson type. Surprisingly, this combination of statistical formalisms unveils the exact probabilities of RILs for any number of genes. Extensions of the framework may have applications in population genetics and beyond. PMID:26196831

  18. Tips and Tricks for Successful Application of Statistical Methods to Biological Data.

    PubMed

    Schlenker, Evelyn

    2016-01-01

    This chapter discusses experimental design and use of statistics to describe characteristics of data (descriptive statistics) and inferential statistics that test the hypothesis posed by the investigator. Inferential statistics, based on probability distributions, depend upon the type and distribution of the data. For data that are continuous, randomly and independently selected, as well as normally distributed more powerful parametric tests such as Student's t test and analysis of variance (ANOVA) can be used. For non-normally distributed or skewed data, transformation of the data (using logarithms) may normalize the data allowing use of parametric tests. Alternatively, with skewed data nonparametric tests can be utilized, some of which rely on data that are ranked prior to statistical analysis. Experimental designs and analyses need to balance between committing type 1 errors (false positives) and type 2 errors (false negatives). For a variety of clinical studies that determine risk or benefit, relative risk ratios (random clinical trials and cohort studies) or odds ratios (case-control studies) are utilized. Although both use 2 × 2 tables, their premise and calculations differ. Finally, special statistical methods are applied to microarray and proteomics data, since the large number of genes or proteins evaluated increase the likelihood of false discoveries. Additional studies in separate samples are used to verify microarray and proteomic data. Examples in this chapter and references are available to help continued investigation of experimental designs and appropriate data analysis. PMID:26585142

  19. A review of statistical methods for protein identification using tandem mass spectrometry

    PubMed Central

    Serang, Oliver; Noble, William

    2012-01-01

    Tandem mass spectrometry has emerged as a powerful tool for the characterization of complex protein samples, an increasingly important problem in biology. The effort to efficiently and accurately perform inference on data from tandem mass spectrometry experiments has resulted in several statistical methods. We use a common framework to describe the predominant methods and discuss them in detail. These methods are classified using the following categories: set cover methods, iterative methods, and Bayesian methods. For each method, we analyze and evaluate the outcome and methodology of published comparisons to other methods; we use this comparison to comment on the qualities and weaknesses, as well as the overall utility, of all methods. We discuss the similarities between these methods and suggest directions for the field that would help unify these similar assumptions in a more rigorous manner and help enable efficient and reliable protein inference. PMID:22833779

  20. Meta-analysis for Discovering Rare-Variant Associations: Statistical Methods and Software Programs

    PubMed Central

    Tang, Zheng-Zheng; Lin, Dan-Yu

    2015-01-01

    There is heightened interest in using next-generation sequencing technologies to identify rare variants that influence complex human diseases and traits. Meta-analysis is essential to this endeavor because large sample sizes are required for detecting associations with rare variants. In this article, we provide a comprehensive overview of statistical methods for meta-analysis of sequencing studies for discovering rare-variant associations. Specifically, we discuss the calculation of relevant summary statistics from participating studies, the construction of gene-level association tests, the choice of transformation for quantitative traits, the use of fixed-effects versus random-effects models, and the removal of shadow association signals through conditional analysis. We also show that meta-analysis based on properly calculated summary statistics is as powerful as joint analysis of individual-participant data. In addition, we demonstrate the performance of different meta-analysis methods by using both simulated and empirical data. We then compare four major software packages for meta-analysis of rare-variant associations—MASS, RAREMETAL, MetaSKAT, and seqMeta—in terms of the underlying statistical methodology, analysis pipeline, and software interface. Finally, we present PreMeta, a software interface that integrates the four meta-analysis packages and allows a consortium to combine otherwise incompatible summary statistics. PMID:26094574

  1. Teaching Statistical Research Methods to Graduate Students: Lessons Learned from Three Different Degree Programs

    ERIC Educational Resources Information Center

    Ekmekci, Ozgur; Hancock, Adrienne B.; Swayze, Susan

    2012-01-01

    This paper examines the challenge of teaching statistical research methods in three master's degree programs at a private university based in Washington, DC. We, as three professors teaching at this university, discuss the way we employ innovative approaches to deal with this challenge. We ground our discussion within the theoretical framework of…

  2. Taguchi statistical design and analysis of cleaning methods for spacecraft materials

    NASA Technical Reports Server (NTRS)

    Lin, Y.; Chung, S.; Kazarians, G. A.; Blosiu, J. O.; Beaudet, R. A.; Quigley, M. S.; Kern, R. G.

    2003-01-01

    In this study, we have extensively tested various cleaning protocols. The variant parameters included the type and concentration of solvent, type of wipe, pretreatment conditions, and various rinsing systems. Taguchi statistical method was used to design and evaluate various cleaning conditions on ten common spacecraft materials.

  3. A Mixed-Methods Assessment of Using an Online Commercial Tutoring System to Teach Introductory Statistics

    ERIC Educational Resources Information Center

    Xu, Yonghong Jade; Meyer, Katrina A.; Morgan, Dianne D.

    2009-01-01

    This study used a mixed-methods approach to evaluate a hybrid teaching format that incorporated an online tutoring system, ALEKS, to address students' learning needs in a graduate-level introductory statistics course. Student performance in the hybrid course with ALEKS was found to be no different from that in a course taught in a traditional…

  4. Demonstrating the Effectiveness of an Integrated and Intensive Research Methods and Statistics Course Sequence

    ERIC Educational Resources Information Center

    Pliske, Rebecca M.; Caldwell, Tracy L.; Calin-Jageman, Robert J.; Taylor-Ritzler, Tina

    2015-01-01

    We developed a two-semester series of intensive (six-contact hours per week) behavioral research methods courses with an integrated statistics curriculum. Our approach includes the use of team-based learning, authentic projects, and Excel and SPSS. We assessed the effectiveness of our approach by examining our students' content area scores on the…

  5. A REVIEW OF STATISTICAL METHODS FOR THE METEOROLOGICAL ADJUSTMENT OF TROPOSPHERIC OZONE. (R825173)

    EPA Science Inventory

    Abstract

    A variety of statistical methods for meteorological adjustment of ozone have been proposed in the literature over the last decade for purposes of forecasting, estimating ozone time trends, or investigating underlying mechanisms from an empirical perspective. T...

  6. Diagnosing Skills of Statistical Hypothesis Testing Using the Rule Space Method

    ERIC Educational Resources Information Center

    Im, Seongah; Yin, Yue

    2009-01-01

    This study illustrated the use of the Rule Space Method to diagnose students' proficiencies in, skills and knowledge of statistical hypothesis testing. Participants included 96 undergraduate and, graduate students, of whom 94 were classified into one or more of the knowledge states identified by, the rule space analysis. Analysis at the level of…

  7. Cooperative Learning in Virtual Environments: The Jigsaw Method in Statistical Courses

    ERIC Educational Resources Information Center

    Vargas-Vargas, Manuel; Mondejar-Jimenez, Jose; Santamaria, Maria-Letica Meseguer; Alfaro-Navarro, Jose-Luis; Fernandez-Aviles, Gema

    2011-01-01

    This document sets out a novel teaching methodology as used in subjects with statistical content, traditionally regarded by students as "difficult". In a virtual learning environment, instructional techniques little used in mathematical courses were employed, such as the Jigsaw cooperative learning method, which had to be adapted to the…

  8. Interpreting Statistical Significance Test Results: A Proposed New "What If" Method.

    ERIC Educational Resources Information Center

    Kieffer, Kevin M.; Thompson, Bruce

    As the 1994 publication manual of the American Psychological Association emphasized, "p" values are affected by sample size. As a result, it can be helpful to interpret the results of statistical significant tests in a sample size context by conducting so-called "what if" analyses. However, these methods can be inaccurate unless "corrected" effect…

  9. Statistical databases

    SciTech Connect

    Kogalovskii, M.R.

    1995-03-01

    This paper presents a review of problems related to statistical database systems, which are wide-spread in various fields of activity. Statistical databases (SDB) are referred to as databases that consist of data and are used for statistical analysis. Topics under consideration are: SDB peculiarities, properties of data models adequate for SDB requirements, metadata functions, null-value problems, SDB compromise protection problems, stored data compression techniques, and statistical data representation means. Also examined is whether the present Database Management Systems (DBMS) satisfy the SDB requirements. Some actual research directions in SDB systems are considered.

  10. Statistical method using operating room information system data to determine anesthetist weekend call requirements.

    PubMed

    Dexter, F; Macario, A; Traub, R D

    2000-02-01

    We present a statistical method that uses data from surgical services information systems to determine the minimum number of anesthetists to be scheduled for weekend call in an operating room suite. The staffing coverage is predicted that provides for sufficient anesthetists to cover each hour of a 24-hour weekend period, while satisfying a specified risk for being understaffed. The statistical method incorporates shifts of varying start times and durations, as well as historical weekend operating room caseload data. By using this method to schedule weekend staff, an anesthesia group can assure as few anesthetists are on call as possible, and for as few hours as possible, while maintaining the level of risk of understaffing that the anesthesia group is willing to accept. An anesthesia group also can use the method to calculate its risk of being understaffed in the surgical suite based on its existing weekend staffing plan. PMID:10876448

  11. a Probability-Based Statistical Method to Extract Water Body of TM Images with Missing Information

    NASA Astrophysics Data System (ADS)

    Lian, Shizhong; Chen, Jiangping; Luo, Minghai

    2016-06-01

    Water information cannot be accurately extracted using TM images because true information is lost in some images because of blocking clouds and missing data stripes, thereby water information cannot be accurately extracted. Water is continuously distributed in natural conditions; thus, this paper proposed a new method of water body extraction based on probability statistics to improve the accuracy of water information extraction of TM images with missing information. Different disturbing information of clouds and missing data stripes are simulated. Water information is extracted using global histogram matching, local histogram matching, and the probability-based statistical method in the simulated images. Experiments show that smaller Areal Error and higher Boundary Recall can be obtained using this method compared with the conventional methods.

  12. Exploratory study on a statistical method to analyse time resolved data obtained during nanomaterial exposure measurements

    NASA Astrophysics Data System (ADS)

    Clerc, F.; Njiki-Menga, G.-H.; Witschger, O.

    2013-04-01

    Most of the measurement strategies that are suggested at the international level to assess workplace exposure to nanomaterials rely on devices measuring, in real time, airborne particles concentrations (according different metrics). Since none of the instruments to measure aerosols can distinguish a particle of interest to the background aerosol, the statistical analysis of time resolved data requires special attention. So far, very few approaches have been used for statistical analysis in the literature. This ranges from simple qualitative analysis of graphs to the implementation of more complex statistical models. To date, there is still no consensus on a particular approach and the current period is always looking for an appropriate and robust method. In this context, this exploratory study investigates a statistical method to analyse time resolved data based on a Bayesian probabilistic approach. To investigate and illustrate the use of the this statistical method, particle number concentration data from a workplace study that investigated the potential for exposure via inhalation from cleanout operations by sandpapering of a reactor producing nanocomposite thin films have been used. In this workplace study, the background issue has been addressed through the near-field and far-field approaches and several size integrated and time resolved devices have been used. The analysis of the results presented here focuses only on data obtained with two handheld condensation particle counters. While one was measuring at the source of the released particles, the other one was measuring in parallel far-field. The Bayesian probabilistic approach allows a probabilistic modelling of data series, and the observed task is modelled in the form of probability distributions. The probability distributions issuing from time resolved data obtained at the source can be compared with the probability distributions issuing from the time resolved data obtained far-field, leading in a

  13. Statistical methods and software for the analysis of highthroughput reverse genetic assays using flow cytometry readouts

    PubMed Central

    Hahne, Florian; Arlt, Dorit; Sauermann, Mamatha; Majety, Meher; Poustka, Annemarie; Wiemann, Stefan; Huber, Wolfgang

    2006-01-01

    Highthroughput cell-based assays with flow cytometric readout provide a powerful technique for identifying components of biologic pathways and their interactors. Interpretation of these large datasets requires effective computational methods. We present a new approach that includes data pre-processing, visualization, quality assessment, and statistical inference. The software is freely available in the Bioconductor package prada. The method permits analysis of large screens to detect the effects of molecular interventions in cellular systems. PMID:16916453

  14. Statistical Method Based on Confidence and Prediction Regions for Analysis of Volatile Organic Compounds in Human Breath Gas

    NASA Astrophysics Data System (ADS)

    Wimmer, G.

    2008-01-01

    In this paper we introduce two confidence and two prediction regions for statistical characterization of concentration measurements of product ions in order to discriminate various groups of persons for prospective better detection of primary lung cancer. Two MATLAB algorithms have been created for more adequate description of concentration measurements of volatile organic compounds in human breath gas for potential detection of primary lung cancer and for evaluation of the appropriate confidence and prediction regions.

  15. Acceleration algorithm for constant-statistics method applied to the nonuniformity correction of infrared sequences

    NASA Astrophysics Data System (ADS)

    Jara Chavez, A. G.; Torres Vicencio, F. O.

    2015-03-01

    Non-uniformity noise, it was, it is, and it will probably be one of the most non-desired attached companion of the infrared focal plane array (IRFPA) data. We present a higher order filter where the key advantage is based in its capacity to estimates the detection parameters and thus to compensate it for fixed pattern noise, as an enhancement of Constant Statistics (CS) theory. This paper shows a technique to improve the convergence in accelerated way for CS (AACS: Acceleration Algorithm for Constant Statistics). The effectiveness of this method is demonstrated by using simulated infrared video sequences and several real infrared video sequences obtained using two infrared cameras.

  16. On the evolution of statistical methods as applied to clinical trials.

    PubMed

    Machin, D

    2004-05-01

    This paper describes how statistical methods have evolved in parallel with activities associated with randomized control trials. In particular we emphasize the pivotal role of two papers published in British Journal of Cancer, and the paper describing the Cox proportional hazards model. In addition, the importance of early papers on estimating the sample size required for trials is highlighted. Later developments including the increasing roles for competing risks, multilevel modelling and Bayesian methodologies are described. The interplay between computer software and statistical methodological developments is stressed. Finally some future directions are indicated. PMID:15078495

  17. A Statistical Method for Reconstructing the Core Location of an Extensive Air Shower

    NASA Astrophysics Data System (ADS)

    Hedayati Kh., H.; Moradi, A.; Emami, M.

    2015-09-01

    Conventional methods of reconstructing extensive air showers (EASs) depend on a lateral density function which itself depends on shower size, age parameter, and core location. In the fitting procedure of a lateral density function to surface array information, the only parameter whose initial value is essential is core location. In this paper, we describe a refined version of a statistical method which can be used to find the initial trial core location of EASs with better precision than the conventional methods. In this method, we use arrival time information of secondary particles for finding not only arrival direction, but also core location.

  18. A statistical method for verifying mesh convergence in Monte Carlo simulations with application to fragmentation

    SciTech Connect

    Bishop, Joseph E.; Strack, O. E.

    2011-03-22

    A novel method is presented for assessing the convergence of a sequence of statistical distributions generated by direct Monte Carlo sampling. The primary application is to assess the mesh or grid convergence, and possibly divergence, of stochastic outputs from non-linear continuum systems. Example systems include those from fluid or solid mechanics, particularly those with instabilities and sensitive dependence on initial conditions or system parameters. The convergence assessment is based on demonstrating empirically that a sequence of cumulative distribution functions converges in the Linfty norm. The effect of finite sample sizes is quantified using confidence levels from the Kolmogorov–Smirnov statistic. The statistical method is independent of the underlying distributions. The statistical method is demonstrated using two examples: (1) the logistic map in the chaotic regime, and (2) a fragmenting ductile ring modeled with an explicit-dynamics finite element code. In the fragmenting ring example the convergence of the distribution describing neck spacing is investigated. The initial yield strength is treated as a random field. Two different random fields are considered, one with spatial correlation and the other without. Both cases converged, albeit to different distributions. The case with spatial correlation exhibited a significantly higher convergence rate compared with the one without spatial correlation.

  19. Novel Method of Interconnect Worstcase Establishment with Statistically-Based Approaches

    NASA Astrophysics Data System (ADS)

    Jung, Won-Young; Kim, Hyungon; Kim, Yong-Ju; Wee, Jae-Kyung

    In order for the interconnect effects due to process-induced variations to be applied to the designs in 0.13μm and below, it is necessary to determine and characterize the realistic interconnect worstcase models with high accuracy and speed. This paper proposes new statistically-based approaches to the characterization of realistic interconnect worstcase models which take into account process-induced variations. The Effective Common Geometry (ECG) and Accumulated Maximum Probability (AMP) algorithms have been developed and implemented into the new statistical interconnect worstcase design environment. To verify this statistical interconnect worstcase design environment, the 31-stage ring oscillators are fabricated and measured with UMC 0.13μm Logic process. The 15-stage ring oscillators are fabricated and measured with 0.18μm standard CMOS process for investigating its flexibility in other technologies. The results show that the relative errors of the new method are less than 1.00%, which is two times more accurate than the conventional worstcase method. Furthermore, the new interconnect worstcase design environment improves optimization speed by 29.61-32.01% compared to that of the conventional worstcase optimization. The new statistical interconnect worstcase design environment accurately predicts the worstcase and bestcase corners of non-normal distribution where conventional methods cannot do well.

  20. Damage diagnosis for SHM of existing civil structure with statistical diagnostic method

    NASA Astrophysics Data System (ADS)

    Iwasaki, Atsushi; Todoroki, Akira; Sugiya, Tsuneya; Sakai, Shinsuke

    2004-07-01

    The present research proposes a new automatic damage diagnostic method that does not require data of damaged state. Structural health monitoring is a noticeable technology for civil structures. Multiple damage diagnostic method for has been proposed, and most of them employ parametric method based on modeling or non-parametric method such as artificial neural networks. These methods demand much costs, and first of all, it is impossible to obtain data for training of damaged existing structures. That causes importance of development of the method, which diagnoses damage just from data of the intact state structure for existing structures. Therefore we purpose new statistical diagnostic method for structural damage detection. In the present method, system identification using a response surface is performed and damage is diagnosed by testing the change of this identified system by statistical test. The new method requires data of non-damaged state and does not require the complicated modeling and data of damaged state structure. As an example, the present study deals damage diagnosis of a jet-fan which installed to a tunnel on an expressway as a ventilator fan. Damages are detected from load of turnbuckles. As a result, the damage is successfully diagnosed with the method.

  1. Application of multivariate statistical methods to the analysis of ancient Turkish potsherds

    SciTech Connect

    Martin, R.C.

    1986-01-01

    Three hundred ancient Turkish potsherds were analyzed by instrumental neutron activation analysis, and the resulting data analyzed by several techniques of multivariate statistical analysis, some only recently developed. The programs AGCLUS, MASLOC, and SIMCA were sequentially employed to characterize and group the samples by type of pottery and site of excavation. Comparison of the statistical analyses by each method provided archaeological insight into the site/type relationships of the samples and ultimately evidence relevant to the commercial relations between the ancient communities and specialization of pottery production over time. The techniques used for statistical analysis were found to be of significant potential utility in the future analysis of other archaeometric data sets. 25 refs., 33 figs.

  2. Comparison of covariate adjustment methods using space-time scan statistics for food animal syndromic surveillance

    PubMed Central

    2013-01-01

    Background Abattoir condemnation data show promise as a rich source of data for syndromic surveillance of both animal and zoonotic diseases. However, inherent characteristics of abattoir condemnation data can bias results from space-time cluster detection methods for disease surveillance, and may need to be accounted for using various adjustment methods. The objective of this study was to compare the space-time scan statistics with different abilities to control for covariates and to assess their suitability for food animal syndromic surveillance. Four space-time scan statistic models were used including: animal class adjusted Poisson, space-time permutation, multi-level model adjusted Poisson, and a weighted normal scan statistic using model residuals. The scan statistics were applied to monthly bovine pneumonic lung and “parasitic liver” condemnation data from Ontario provincial abattoirs from 2001–2007. Results The number and space-time characteristics of identified clusters often varied between space-time scan tests for both “parasitic liver” and pneumonic lung condemnation data. While there were some similarities between isolated clusters in space, time and/or space-time, overall the results from space-time scan statistics differed substantially depending on the covariate adjustment approach used. Conclusions Variability in results among methods suggests that caution should be used in selecting space-time scan methods for abattoir surveillance. Furthermore, validation of different approaches with simulated or real outbreaks is required before conclusive decisions can be made concerning the best approach for conducting surveillance with these data. PMID:24246040

  3. A new mathematical evaluation of smoking problem based of algebraic statistical method.

    PubMed

    Mohammed, Maysaa J; Rakhimov, Isamiddin S; Shitan, Mahendran; Ibrahim, Rabha W; Mohammed, Nadia F

    2016-01-01

    Smoking problem is considered as one of the hot topics for many years. In spite of overpowering facts about the dangers, smoking is still a bad habit widely spread and socially accepted. Many people start smoking during their gymnasium period. The discovery of the dangers of smoking gave a warning sign of danger for individuals. There are different statistical methods used to analyze the dangers of smoking. In this study, we apply an algebraic statistical method to analyze and classify real data using Markov basis for the independent model on the contingency table. Results show that the Markov basis based classification is able to distinguish different date elements. Moreover, we check our proposed method via information theory by utilizing the Shannon formula to illustrate which one of these alternative tables is the best in term of independent. PMID:26858555

  4. A parsimonious statistical method to detect groupwise differentially expressed functional connectivity networks.

    PubMed

    Chen, Shuo; Kang, Jian; Xing, Yishi; Wang, Guoqing

    2015-12-01

    Group-level functional connectivity analyses often aim to detect the altered connectivity patterns between subgroups with different clinical or psychological experimental conditions, for example, comparing cases and healthy controls. We present a new statistical method to detect differentially expressed connectivity networks with significantly improved power and lower false-positive rates. The goal of our method was to capture most differentially expressed connections within networks of constrained numbers of brain regions (by the rule of parsimony). By virtue of parsimony, the false-positive individual connectivity edges within a network are effectively reduced, whereas the informative (differentially expressed) edges are allowed to borrow strength from each other to increase the overall power of the network. We develop a test statistic for each network in light of combinatorics graph theory, and provide p-values for the networks (in the weak sense) by using permutation test with multiple-testing adjustment. We validate and compare this new approach with existing methods, including false discovery rate and network-based statistic, via simulation studies and a resting-state functional magnetic resonance imaging case-control study. The results indicate that our method can identify differentially expressed connectivity networks, whereas existing methods are limited. PMID:26416398

  5. Automated counting of morphologically normal red blood cells by using digital holographic microscopy and statistical methods

    NASA Astrophysics Data System (ADS)

    Moon, Inkyu; Yi, Faliu

    2015-09-01

    In this paper we overview a method to automatically count morphologically normal red blood cells (RBCs) by using off-axis digital holographic microscopy and statistical methods. Three kinds of RBC are used as training and testing data. All of the RBC phase images are obtained with digital holographic microscopy (DHM) that is robust to transparent or semitransparent biological cells. For the determination of morphologically normal RBCs, the RBC's phase images are first segmented with marker-controlled watershed transform algorithm. Multiple features are extracted from the segmented cells. Moreover, the statistical method of Hotelling's T-square test is conducted to show that the 3D features from 3D imaging method can improve the discrimination performance for counting of normal shapes of RBCs. Finally, the classifier is designed by using statistical Bayesian algorithm and the misclassification rates are measured with leave-one-out technique. Experimental results show the feasibility of the classification method for calculating the percentage of each typical normal RBC shape.

  6. Feature-based and statistical methods for analyzing the Deepwater Horizon oil spill with AVIRIS imagery

    USGS Publications Warehouse

    Rand, R.S.; Clark, R.N.; Livo, K.E.

    2011-01-01

    The Deepwater Horizon oil spill covered a very large geographical area in the Gulf of Mexico creating potentially serious environmental impacts on both marine life and the coastal shorelines. Knowing the oil's areal extent and thickness as well as denoting different categories of the oil's physical state is important for assessing these impacts. High spectral resolution data in hyperspectral imagery (HSI) sensors such as Airborne Visible and Infrared Imaging Spectrometer (AVIRIS) provide a valuable source of information that can be used for analysis by semi-automatic methods for tracking an oil spill's areal extent, oil thickness, and oil categories. However, the spectral behavior of oil in water is inherently a highly non-linear and variable phenomenon that changes depending on oil thickness and oil/water ratios. For certain oil thicknesses there are well-defined absorption features, whereas for very thin films sometimes there are almost no observable features. Feature-based imaging spectroscopy methods are particularly effective at classifying materials that exhibit specific well-defined spectral absorption features. Statistical methods are effective at classifying materials with spectra that exhibit a considerable amount of variability and that do not necessarily exhibit well-defined spectral absorption features. This study investigates feature-based and statistical methods for analyzing oil spills using hyperspectral imagery. The appropriate use of each approach is investigated and a combined feature-based and statistical method is proposed. ?? 2011 SPIE.

  7. A Statistical Approach for the Concurrent Coupling of Molecular Dynamics and Finite Element Methods

    NASA Technical Reports Server (NTRS)

    Saether, E.; Yamakov, V.; Glaessgen, E.

    2007-01-01

    Molecular dynamics (MD) methods are opening new opportunities for simulating the fundamental processes of material behavior at the atomistic level. However, increasing the size of the MD domain quickly presents intractable computational demands. A robust approach to surmount this computational limitation has been to unite continuum modeling procedures such as the finite element method (FEM) with MD analyses thereby reducing the region of atomic scale refinement. The challenging problem is to seamlessly connect the two inherently different simulation techniques at their interface. In the present work, a new approach to MD-FEM coupling is developed based on a restatement of the typical boundary value problem used to define a coupled domain. The method uses statistical averaging of the atomistic MD domain to provide displacement interface boundary conditions to the surrounding continuum FEM region, which, in return, generates interface reaction forces applied as piecewise constant traction boundary conditions to the MD domain. The two systems are computationally disconnected and communicate only through a continuous update of their boundary conditions. With the use of statistical averages of the atomistic quantities to couple the two computational schemes, the developed approach is referred to as an embedded statistical coupling method (ESCM) as opposed to a direct coupling method where interface atoms and FEM nodes are individually related. The methodology is inherently applicable to three-dimensional domains, avoids discretization of the continuum model down to atomic scales, and permits arbitrary temperatures to be applied.

  8. A Parsimonious Statistical Method to Detect Groupwise Differentially Expressed Functional Connectivity Networks

    PubMed Central

    Chen, Shuo; Kang, Jian; Xing, Yishi; Wang, Guoqing

    2016-01-01

    Group-level functional connectivity analyses often aim to detect the altered connectivity patterns between subgroups with different clinical or psychological experimental conditions, for example, comparing cases and healthy controls. We present a new statistical method to detect differentially expressed connectivity networks with significantly improved power and lower false-positive rates. The goal of our method was to capture most differentially expressed connections within networks of constrained numbers of brain regions (by the rule of parsimony). By virtue of parsimony, the false-positive individual connectivity edges within a network are effectively reduced, whereas the informative (differentially expressed) edges are allowed to borrow strength from each other to increase the overall power of the network. We develop a test statistic for each network in light of combinatorics graph theory, and provide p-values for the networks (in the weak sense) by using permutation test with multiple-testing adjustment. We validate and compare this new approach with existing methods, including false discovery rate and network-based statistic, via simulation studies and a resting-state functional magnetic resonance imaging case–control study. The results indicate that our method can identify differentially expressed connectivity networks, whereas existing methods are limited. PMID:26416398

  9. Adequate supervision for children and adolescents.

    PubMed

    Anderst, James; Moffatt, Mary

    2014-11-01

    Primary care providers (PCPs) have the opportunity to improve child health and well-being by addressing supervision issues before an injury or exposure has occurred and/or after an injury or exposure has occurred. Appropriate anticipatory guidance on supervision at well-child visits can improve supervision of children, and may prevent future harm. Adequate supervision varies based on the child's development and maturity, and the risks in the child's environment. Consideration should be given to issues as wide ranging as swimming pools, falls, dating violence, and social media. By considering the likelihood of harm and the severity of the potential harm, caregivers may provide adequate supervision by minimizing risks to the child while still allowing the child to take "small" risks as needed for healthy development. Caregivers should initially focus on direct (visual, auditory, and proximity) supervision of the young child. Gradually, supervision needs to be adjusted as the child develops, emphasizing a safe environment and safe social interactions, with graduated independence. PCPs may foster adequate supervision by providing concrete guidance to caregivers. In addition to preventing injury, supervision includes fostering a safe, stable, and nurturing relationship with every child. PCPs should be familiar with age/developmentally based supervision risks, adequate supervision based on those risks, characteristics of neglectful supervision based on age/development, and ways to encourage appropriate supervision throughout childhood. PMID:25369578

  10. Small Rural Schools CAN Have Adequate Curriculums.

    ERIC Educational Resources Information Center

    Loustaunau, Martha

    The small rural school's foremost and largest problem is providing an adequate curriculum for students in a changing world. Often the small district cannot or is not willing to pay the per-pupil cost of curriculum specialists, specialized courses using expensive equipment no more than one period a day, and remodeled rooms to accommodate new…

  11. Funding the Formula Adequately in Oklahoma

    ERIC Educational Resources Information Center

    Hancock, Kenneth

    2015-01-01

    This report is a longevity, simulational study that looks at how the ratio of state support to local support effects the number of school districts that breaks the common school's funding formula which in turns effects the equity of distribution to the common schools. After nearly two decades of adequately supporting the funding formula, Oklahoma…

  12. Assessing the impact of vaccination programmes on burden of disease: Underlying complexities and statistical methods.

    PubMed

    Mealing, Nicole; Hayen, Andrew; Newall, Anthony T

    2016-06-01

    It is important to assess the impact a vaccination programme has on the burden of disease after it is implemented. For example, this may reveal herd immunity effects or vaccine-induced shifts in the incidence of disease or in circulating strains or serotypes of the pathogen. In this article we summarise the key features of infectious diseases that need to be considered when trying to detect any changes in the burden of diseases at a population level as a result of vaccination efforts. We outline the challenges of using routine surveillance databases to monitor infectious diseases, such as the identification of diseased cases and the availability of vaccination status for cases. We highlight the complexities in modelling the underlying patterns in infectious disease rates (e.g. presence of autocorrelation) and discuss the main statistical methods that can be used to control for periodicity (e.g. seasonality) and autocorrelation when assessing the impact of vaccination programmes on burden of disease (e.g. cosinor terms, generalised additive models, autoregressive processes and moving averages). For some analyses, there may be multiple methods that can be used, but it is important for authors to justify the method chosen and discuss any limitations. We present a case study review of the statistical methods used in the literature to assess the rotavirus vaccination programme impact in Australia. The methods used varied and included generalised linear models and descriptive statistics. Not all studies accounted for autocorrelation and seasonality, which can have a major influence on results. We recommend that future analyses consider the strength and weakness of alternative statistical methods and justify their choice. PMID:27156635

  13. Quantification and Statistical Analysis Methods for Vessel Wall Components from Stained Images with Masson's Trichrome

    PubMed Central

    Hernández-Morera, Pablo; Castaño-González, Irene; Travieso-González, Carlos M.; Mompeó-Corredera, Blanca; Ortega-Santana, Francisco

    2016-01-01

    Purpose To develop a digital image processing method to quantify structural components (smooth muscle fibers and extracellular matrix) in the vessel wall stained with Masson’s trichrome, and a statistical method suitable for small sample sizes to analyze the results previously obtained. Methods The quantification method comprises two stages. The pre-processing stage improves tissue image appearance and the vessel wall area is delimited. In the feature extraction stage, the vessel wall components are segmented by grouping pixels with a similar color. The area of each component is calculated by normalizing the number of pixels of each group by the vessel wall area. Statistical analyses are implemented by permutation tests, based on resampling without replacement from the set of the observed data to obtain a sampling distribution of an estimator. The implementation can be parallelized on a multicore machine to reduce execution time. Results The methods have been tested on 48 vessel wall samples of the internal saphenous vein stained with Masson’s trichrome. The results show that the segmented areas are consistent with the perception of a team of doctors and demonstrate good correlation between the expert judgments and the measured parameters for evaluating vessel wall changes. Conclusion The proposed methodology offers a powerful tool to quantify some components of the vessel wall. It is more objective, sensitive and accurate than the biochemical and qualitative methods traditionally used. The permutation tests are suitable statistical techniques to analyze the numerical measurements obtained when the underlying assumptions of the other statistical techniques are not met. PMID:26761643

  14. [Identification of Staphylococcus aureus by determining nuclease activity and using methods of multivariate statistical analysis].

    PubMed

    Generalova, A G; Berzhets, V M; Novikov, D K; Generalov, I I

    1998-01-01

    A new quantitative method for the determination of the DNA-se activity of bacteria, based on the prevention of the clot formation of DNA with rivanol under the action of microbial DNA-ses, has been developed. The sensitivity of this method is 0.005-0.01 units of activity (1-2 ng) of the enzyme in a sample for 1 hour of incubation; the variation coefficient of the method is 8-9%. The use of this method has made it possible to reduce the time of the identification of S.aureus by 2-3 days in comparison with the commonly used methods. As revealed on the model of differentiation between S.aureus and S.epidermidis, the methods of multivariate statistical analysis (dispersion, discriminant, cluster methods) may find wide application for the discrimination of bacteria. They are supposed to be used for the interspecific identification of coagulase-negative staphylococci. PMID:9700871

  15. New Methods for Applying Statistical State Dynamics to Problems in Atmospheric Turbulence

    NASA Astrophysics Data System (ADS)

    Farrell, B.; Ioannou, P. J.

    2015-12-01

    Adopting the perspective of statistical state dynamics (SSD) has led to a number of recent advances inunderstanding and simulating atmospheric turbulence at both boundary layer and planetary scale. Traditionally, realizations have been used to study turbulence and if a statistical quantity was needed it was obtained by averaging. However, it is now becomimg more widely appreciated that there are important advantages to studying the statistical state dynamics (SSD) directly. In turbulent systems statistical quantities are often the most useful and the advantage of obtaining these quantities directly as state variables is obvious. Moreover, quantities such as the probability density function (pdf) are often difficult to obtain accurately by sampling state trajectories. In the event that the pdf is itself time dependent or even chaotic, as is the case in the turbulence of the planetary boundary layer, the pdf can only be obtained as a state variable. However, perhaps the greatest advantage of the SSD approach is that it reveals directly the essential cooperative mechanisms of interaction among spatial and temporal scales that underly the turbulent state. In order to exploit these advantages of the SSD approach to geophysical turbulence, new analytical and computational methods are being developed. Example problems in atmospheric turbulence will be presented in which these new SSD analysis and computational methods are used.

  16. Proposal for a biometrics of the cortical surface: a statistical method for relative surface distance metrics

    NASA Astrophysics Data System (ADS)

    Bookstein, Fred L.

    1995-08-01

    Recent advances in computational geometry have greatly extended the range of neuroanatomical questions that can be approached by rigorous quantitative methods. One of the major current challenges in this area is to describe the variability of human cortical surface form and its implications for individual differences in neurophysiological functioning. Existing techniques for representation of stochastically invaginated surfaces do not conduce to the necessary parametric statistical summaries. In this paper, following a hint from David Van Essen and Heather Drury, I sketch a statistical method customized for the constraints of this complex data type. Cortical surface form is represented by its Riemannian metric tensor and averaged according to parameters of a smooth averaged surface. Sulci are represented by integral trajectories of the smaller principal strains of this metric, and their statistics follow the statistics of that relative metric. The diagrams visualizing this tensor analysis look like alligator leather but summarize all aspects of cortical surface form in between the principal sulci, the reliable ones; no flattening is required.

  17. A combined approach to the estimation of statistical error of the direct simulation Monte Carlo method

    NASA Astrophysics Data System (ADS)

    Plotnikov, M. Yu.; Shkarupa, E. V.

    2015-11-01

    Presently, the direct simulation Monte Carlo (DSMC) method is widely used for solving rarefied gas dynamics problems. As applied to steady-state problems, a feature of this method is the use of dependent sample values of random variables for the calculation of macroparameters of gas flows. A new combined approach to estimating the statistical error of the method is proposed that does not practically require additional computations, and it is applicable for any degree of probabilistic dependence of sample values. Features of the proposed approach are analyzed theoretically and numerically. The approach is tested using the classical Fourier problem and the problem of supersonic flow of rarefied gas through permeable obstacle.

  18. An iterative method for the solution of the statistical and radiative equilibrium equations in expanding atmospheres

    NASA Astrophysics Data System (ADS)

    Hillier, D. J.

    1990-05-01

    A method for the solution of the statistical equilibrium, and radiative equilibrium equations in spherical atmospheres is presented. The iterative scheme uses a tridiagonal (or pentadiagonal) Newton-Raphson operator, and is based on the complete linearization method of Auer and Mihalas (1969) but requires less memory, and imposes no limit on the number of transitions that can be treated. The method is also related to iterative techniques that use approximate diagonal lambda operators but it has a vastly superior convergence rate. Calculations of WN and WC model atmospheres illustrate the excellent rate of convergence.

  19. Damage identification in beam type structures based on statistical moment using a two step method

    NASA Astrophysics Data System (ADS)

    Wang, Dansheng; Xiang, Wei; Zhu, Hongping

    2014-02-01

    This paper defines a novel damage index-strain statistical moment, and formulates the fourth strain statistical moment (FSSM) of beam-type structures under white noise excitation. Based on this newly defined strain statistical moment index and the least square optimization algorithm, a two-step damage identification method is proposed. This two-step method is operated like this: first use the difference curves of FSSMs before and after damage to locate damage elements; then for those identified damage elements, employ the model updating method based on the least square algorithm to assess their damage severity. Numerical studies on a simply supported beam and a two-span continuous beam are performed and the study results show that the newly defined index is effective to locate damages, even when the noise intensity is as high as 15 percent. Integrating with the least square-based model updating technique, the damage severities of beam-type structures can also be determined quantitatively. In this way, the proposed two-step method is verified and found to be capable of identifying damage positions and severities of beam-type structures and insensitive to measurement noise.

  20. Trends in Citations to Books on Epidemiological and Statistical Methods in the Biomedical Literature

    PubMed Central

    Porta, Miquel; Vandenbroucke, Jan P.; Ioannidis, John P. A.; Sanz, Sergio; Fernandez, Esteve; Bhopal, Raj; Morabia, Alfredo; Victora, Cesar; Lopez, Tomàs

    2013-01-01

    Background There are no analyses of citations to books on epidemiological and statistical methods in the biomedical literature. Such analyses may shed light on how concepts and methods changed while biomedical research evolved. Our aim was to analyze the number and time trends of citations received from biomedical articles by books on epidemiological and statistical methods, and related disciplines. Methods and Findings The data source was the Web of Science. The study books were published between 1957 and 2010. The first year of publication of the citing articles was 1945. We identified 125 books that received at least 25 citations. Books first published in 1980–1989 had the highest total and median number of citations per year. Nine of the 10 most cited texts focused on statistical methods. Hosmer & Lemeshow's Applied logistic regression received the highest number of citations and highest average annual rate. It was followed by books by Fleiss, Armitage, et al., Rothman, et al., and Kalbfleisch and Prentice. Fifth in citations per year was Sackett, et al., Evidence-based medicine. The rise of multivariate methods, clinical epidemiology, or nutritional epidemiology was reflected in the citation trends. Educational textbooks, practice-oriented books, books on epidemiological substantive knowledge, and on theory and health policies were much less cited. None of the 25 top-cited books had the theoretical or sociopolitical scope of works by Cochrane, McKeown, Rose, or Morris. Conclusions Books were mainly cited to reference methods. Books first published in the 1980s continue to be most influential. Older books on theory and policies were rooted in societal and general medical concerns, while the most modern books are almost purely on methods. PMID:23667447

  1. Data Mining Methods Applied to Flight Operations Quality Assurance Data: A Comparison to Standard Statistical Methods

    NASA Technical Reports Server (NTRS)

    Stolzer, Alan J.; Halford, Carl

    2007-01-01

    In a previous study, multiple regression techniques were applied to Flight Operations Quality Assurance-derived data to develop parsimonious model(s) for fuel consumption on the Boeing 757 airplane. The present study examined several data mining algorithms, including neural networks, on the fuel consumption problem and compared them to the multiple regression results obtained earlier. Using regression methods, parsimonious models were obtained that explained approximately 85% of the variation in fuel flow. In general data mining methods were more effective in predicting fuel consumption. Classification and Regression Tree methods reported correlation coefficients of .91 to .92, and General Linear Models and Multilayer Perceptron neural networks reported correlation coefficients of about .99. These data mining models show great promise for use in further examining large FOQA databases for operational and safety improvements.

  2. Evaluating differences of metabolic performances: statistical methods and their application to animal cell cultivations.

    PubMed

    Hädicke, O; Lohr, V; Genzel, Y; Reichl, U; Klamt, S

    2013-10-01

    In cell culture process development, monitoring and analyzing metabolic key parameters is routinely applied to demonstrate specific advantages of one experimental setup over another. It is of great importance that the observed differences and expected improvements are practically relevant and statistically significant. However, a systematic assessment whether observed differences in metabolic rates are statistically significant or not is often missing. This can lead to time-consuming and costly changes of an established biotechnological process due to false positive results. In the present work we demonstrate how well-established statistical tools can be employed to analyze systematically different sources of variations in metabolic rate determinations and to assess, in an unbiased way, their implications on the significance of the observed differences. As a case study, we evaluate differing growth characteristics and metabolic rates of the avian designer cell line AGE1.CR.pIX cultivated in a stirred tank reactor and in a wave bioreactor. Although large differences in metabolic rates and cell growth were expected (due to different aeration, agitation, pH-control, etc.) and partially observed (up to 79%), our results show that the inter-experimental variance between experiments performed under identical conditions but with different pre-cultures is a major contributor to the overall variance of metabolic rates. The lower bounds of the overall relative standard deviations for specific metabolic rates were between 4% and 73%. The application of available statistical methods revealed that the observed differences were statistically not significant and consequently insufficient to confirm relevant differences between both cultivation systems. Our study provides a general guideline for statistical analyses in comparative cultivation studies and emphasizes the necessity to account for the inter-experimental variance (mainly caused by biological variation) to avoid false

  3. Statistical damage detection method for frame structures using a confidence interval

    NASA Astrophysics Data System (ADS)

    Li, Weiming; Zhu, Hongping; Luo, Hanbin; Xia, Yong

    2010-03-01

    A novel damage detection method is applied to a 3-story frame structure, to obtain statistical quantification control criterion of the existence, location and identification of damage. The mean, standard deviation, and exponentially weighted moving average (EWMA) are applied to detect damage information according to statistical process control (SPC) theory. It is concluded that the detection is insignificant with the mean and EWMA because the structural response is not independent and is not a normal distribution. On the other hand, the damage information is detected well with the standard deviation because the influence of the data distribution is not pronounced with this parameter. A suitable moderate confidence level is explored for more significant damage location and quantification detection, and the impact of noise is investigated to illustrate the robustness of the method.

  4. Statistical and optimization methods to expedite neural network training for transient identification

    SciTech Connect

    Reifman, J.; Vitela, E.J.; Lee, J.C.

    1993-03-01

    Two complementary methods, statistical feature selection and nonlinear optimization through conjugate gradients, are used to expedite feedforward neural network training. Statistical feature selection techniques in the form of linear correlation coefficients and information-theoretic entropy are used to eliminate redundant and non-informative plant parameters to reduce the size of the network. The method of conjugate gradients is used to accelerate the network training convergence and to systematically calculate the Teaming and momentum constants at each iteration. The proposed techniques are compared with the backpropagation algorithm using the entire set of plant parameters in the training of neural networks to identify transients simulated with the Midland Nuclear Power Plant Unit 2 simulator. By using 25% of the plant parameters and the conjugate gradients, a 30-fold reduction in CPU time was obtained without degrading the diagnostic ability of the network.

  5. Statistical and optimization methods to expedite neural network training for transient identification

    SciTech Connect

    Reifman, J. . Reactor Analysis Div.); Vitela, E.J. . Inst. de Ciencias Nucleares); Lee, J.C. . Dept. of Nuclear Engineering)

    1993-01-01

    Two complementary methods, statistical feature selection and nonlinear optimization through conjugate gradients, are used to expedite feedforward neural network training. Statistical feature selection techniques in the form of linear correlation coefficients and information-theoretic entropy are used to eliminate redundant and non-informative plant parameters to reduce the size of the network. The method of conjugate gradients is used to accelerate the network training convergence and to systematically calculate the Teaming and momentum constants at each iteration. The proposed techniques are compared with the backpropagation algorithm using the entire set of plant parameters in the training of neural networks to identify transients simulated with the Midland Nuclear Power Plant Unit 2 simulator. By using 25% of the plant parameters and the conjugate gradients, a 30-fold reduction in CPU time was obtained without degrading the diagnostic ability of the network.

  6. Statistical and numerical methods to improve the transient divided bar method

    NASA Astrophysics Data System (ADS)

    Bording, Thue; Bom Nielsen, Søren; Balling, Niels

    2014-05-01

    A key element in studying subsurface heat transfer processes is accurate knowledge of the thermal properties. These properties include thermal conductivity, thermal diffusivity and heat capacity. The divided bar method is a commonly used method to estimate thermal conductivity of rock samples. In the method's simplest form, a fixed temperature difference is imposed on a stack consisting of the rock sample and a standard material with known thermal conductivity. Temperature measurements along the stack are used to estimate the temperature gradients and the thermal conductivity of the sample can then be found by Fourier's law. We present several improvements to this method that allows for simultaneous measurements of both thermal conductivity and thermal diffusivity. The divided bar setup is run in a transient mode, and a time-dependent temperature profile is measured at four points along the stack: on either side of the sample and at the top and bottom of the stack. To induce a thermal signal, a time-varying temperature is imposed at one end of the stack during measurements. Using the measured temperatures at both ends as Dirichlet boundary conditions, a finite element procedure is used to model the temperature profile. This procedure is used as the forward model. A Markov Chain Monte Carlo Metropolis Hastings algorithm is used for the inversion modelling. The unknown parameters are thermal conductivity and volumetric heat capacity of the sample and the contact resistances between the elements in the stack. The contact resistances are not resolved and must be made as small as possible by careful sample preparation and stack assembly. Histograms of the unknown parameters are produced. The ratio of thermal conductivity and volumetric heat capacity yields a histogram of thermal diffusivity. Since density can be measured independently, the specific heat capacity is also obtained. The main improvement with this method is that not only are we able to measure thermal

  7. Wave climate projections along the French coastline: Dynamical versus statistical downscaling methods

    NASA Astrophysics Data System (ADS)

    Laugel, Amélie; Menendez, Melisa; Benoit, Michel; Mattarolo, Giovanni; Méndez, Fernando

    2014-12-01

    The estimation of possible impacts related to climate change on the wave climate is subject to several levels of uncertainty. In this work, we focus on the uncertainties inherent in the method applied to project the wave climate using atmospheric simulations. Two approaches are commonly used to obtain the regional wave climate: dynamical and statistical downscaling from atmospheric data. We apply both approaches based on the outputs of a global climate model (GCM), ARPEGE-CLIMAT, under three possible future scenarios (B1, A1B and A2) of the Fourth Assessment Report, AR4 (IPCC, 2007), along the French coast and evaluate their results for the wave climate with a high level of precision. The performance of the dynamical and the statistical methods is determined through a comparative analysis of the estimated means, standard deviations and monthly quantile distributions of significant wave heights, the joint probability distributions of wave parameters and seasonal and interannual variability. Analysis of the results shows that the statistical projections are able to reproduce the wave climatology as well as the dynamical projections, with some deficiencies being observed in the summer and for the upper tail of the significant wave height. In addition, with its low computational time requirements, the statistical downscaling method allows an ensemble of simulations to be calculated faster than the dynamical method. It then becomes possible to quantify the uncertainties associated with the choice of the GCM or the socio-economic scenarios, which will improve estimates of the impact of wave climate change along the French coast.

  8. A Framework for the Economic Analysis of Data Collection Methods for Vital Statistics

    PubMed Central

    Jimenez-Soto, Eliana; Hodge, Andrew; Nguyen, Kim-Huong; Dettrick, Zoe; Lopez, Alan D.

    2014-01-01

    Background Over recent years there has been a strong movement towards the improvement of vital statistics and other types of health data that inform evidence-based policies. Collecting such data is not cost free. To date there is no systematic framework to guide investment decisions on methods of data collection for vital statistics or health information in general. We developed a framework to systematically assess the comparative costs and outcomes/benefits of the various data methods for collecting vital statistics. Methodology The proposed framework is four-pronged and utilises two major economic approaches to systematically assess the available data collection methods: cost-effectiveness analysis and efficiency analysis. We built a stylised example of a hypothetical low-income country to perform a simulation exercise in order to illustrate an application of the framework. Findings Using simulated data, the results from the stylised example show that the rankings of the data collection methods are not affected by the use of either cost-effectiveness or efficiency analysis. However, the rankings are affected by how quantities are measured. Conclusion There have been several calls for global improvements in collecting useable data, including vital statistics, from health information systems to inform public health policies. Ours is the first study that proposes a systematic framework to assist countries undertake an economic evaluation of DCMs. Despite numerous challenges, we demonstrate that a systematic assessment of outputs and costs of DCMs is not only necessary, but also feasible. The proposed framework is general enough to be easily extended to other areas of health information. PMID:25171152

  9. Hourly Precipitation Downscaling With Empirical Statistical Methods: Case Study near the US Eastern Coast

    NASA Astrophysics Data System (ADS)

    Wang, Y.; Sivandran, G.

    2014-12-01

    Statistical downscaling methods are widely used to reconcile the spatial and temporal difference between climate model outputs and input requirements of climate change impact assessments. Quantile-mapping, due to its simplicity and general good performance, is one of the most popular. However, its simplicity also leads to variations in the procedure among studies, and it is not always well cross-validated. There is also less attention paid to sub-daily precipitation downscaling which is important for urban hydrologic purposes. The study explores the potential of quantile-mapping by comparing four of its variations, and extends its application by linking it to an hourly k nearest-neighbor resampling disaggregation. The methods are trained with NCEP/NCAR 40-year reanalysis. Seven-fold cross-validation on various mean, variability, and extreme precipitation statistics is performed with hourly observations at rain gauges along the eastern coast of the United States. The best performance on mean monthly precipitation and annual maximum 5-day precipitation is found when quantile-mapping is trained without regard to seasonality. However, the best performance on all other statistics is contingent upon the method being trained separately for each month and combined with a monthly bias-correction factor. Deficiencies in quantile-mapping carry over to the hourly disaggregation step. When the downscaled daily precipitation is satisfactory, the hourly disaggregation performs very well on all statistics after careful selection of its two parameters. These results demonstrate the importance to consider seasonality in the implementation of quantile-mapping and highlight some clear, though limited, deficiencies. That it is feasible to generate realistic hourly precipitation series with easy-to-implement empirical methods is also of interest to water managers.

  10. Building an Effective Speech Corpus by Utilizing Statistical Multidimensional Scaling Method

    NASA Astrophysics Data System (ADS)

    Nagino, Goshu; Shozakai, Makoto; Toda, Tomoki; Saruwatari, Hiroshi; Shikano, Kiyohiro

    This paper proposes a technique for building an effective speech corpus with lower cost by utilizing a statistical multidimensional scaling method. The statistical multidimensional scaling method visualizes multiple HMM acoustic models into two-dimensional space. At first, a small number of voice samples per speaker is collected; speaker adapted acoustic models trained with collected utterances, are mapped into two-dimensional space by utilizing the statistical multidimensional scaling method. Next, speakers located in the periphery of the distribution, in a plotted map are selected; a speech corpus is built by collecting enough voice samples for the selected speakers. In an experiment for building an isolated-word speech corpus, the performance of an acoustic model trained with 200 selected speakers was equivalent to that of an acoustic model trained with 533 non-selected speakers. It means that a cost reduction of more than 62% was achieved. In an experiment for building a continuous word speech corpus, the performance of an acoustic model trained with 500 selected speakers was equivalent to that of an acoustic model trained with 1179 non-selected speakers. It means that a cost reduction of more than 57% was achieved.

  11. Fault diagnosis of rotating machinery with a novel statistical feature extraction and evaluation method

    NASA Astrophysics Data System (ADS)

    Li, Wei; Zhu, Zhencai; Jiang, Fan; Zhou, Gongbo; Chen, Guoan

    2015-01-01

    Fault diagnosis of rotating machinery is receiving more and more attentions. Vibration signals of rotating machinery are commonly analyzed to extract features of faults, and the features are identified with classifiers, e.g. artificial neural networks (ANNs) and support vector machines (SVMs). Due to nonlinear behaviors and unknown noises in machinery, the extracted features are varying from sample to sample, which may result in false classifications. It is also difficult to analytically ensure the accuracy of fault diagnosis. In this paper, a feature extraction and evaluation method is proposed for fault diagnosis of rotating machinery. Based on the central limit theory, an extraction procedure is given to obtain the statistical features with the help of existing signal processing tools. The obtained statistical features approximately obey normal distributions. They can significantly improve the performance of fault classification, and it is verified by taking ANN and SVM classifiers as examples. Then the statistical features are evaluated with a decoupling technique and compared with thresholds to make the decision on fault classification. The proposed evaluation method only requires simple algebraic computation, and the accuracy of fault classification can be analytically guaranteed in terms of the so-called false classification rate (FCR). An experiment is carried out to verify the effectiveness of the proposed method, where the unbalanced fault of rotor, inner race fault, outer race fault and ball fault of bearings are considered.

  12. Statistical Methods for Estimation of Direct and Differential Kinematics of the Vocal Tract

    PubMed Central

    Lammert, Adam; Goldstein, Louis; Narayanan, Shrikanth; Iskarous, Khalil

    2012-01-01

    We present and evaluate two statistical methods for estimating kinematic relationships of the speech production system: Artificial Neural Networks and Locally-Weighted Regression. The work is motivated by the need to characterize this motor system, with particular focus on estimating differential aspects of kinematics. Kinematic analysis will facilitate progress in a variety of areas, including the nature of speech production goals, articulatory redundancy and, relatedly, acoustic-to-articulatory inversion. Statistical methods must be used to estimate these relationships from data since they are infeasible to express in closed form. Statistical models are optimized and evaluated – using a heldout data validation procedure – on two sets of synthetic speech data. The theoretical and practical advantages of both methods are also discussed. It is shown that both direct and differential kinematics can be estimated with high accuracy, even for complex, nonlinear relationships. Locally-Weighted Regression displays the best overall performance, which may be due to practical advantages in its training procedure. Moreover, accurate estimation can be achieved using only a modest amount of training data, as judged by convergence of performance. The algorithms are also applied to real-time MRI data, and the results are generally consistent with those obtained from synthetic data. PMID:24052685

  13. Identifying minefields and verifying clearance: adapting statistical methods for UXO target detection

    NASA Astrophysics Data System (ADS)

    Gilbert, Richard O.; O'Brien, Robert F.; Wilson, John E.; Pulsipher, Brent A.; McKinstry, Craig A.

    2003-09-01

    It may not be feasible to completely survey large tracts of land suspected of containing minefields. It is desirable to develop a characterization protocol that will confidently identify minefields within these large land tracts if they exist. Naturally, surveying areas of greatest concern and most likely locations would be necessary but will not provide the needed confidence that an unknown minefield had not eluded detection. Once minefields are detected, methods are needed to bound the area that will require detailed mine detection surveys. The US Department of Defense Strategic Environmental Research and Development Program (SERDP) is sponsoring the development of statistical survey methods and tools for detecting potential UXO targets. These methods may be directly applicable to demining efforts. Statistical methods are employed to determine the optimal geophysical survey transect spacing to have confidence of detecting target areas of a critical size, shape, and anomaly density. Other methods under development determine the proportion of a land area that must be surveyed to confidently conclude that there are no UXO present. Adaptive sampling schemes are also being developed as an approach for bounding the target areas. These methods and tools will be presented and the status of relevant research in this area will be discussed.

  14. Evaluation of Statistical Rainfall Disaggregation Methods Using Rain-Gauge Information for West-Central Florida

    SciTech Connect

    Murch, Renee Rokicki; Zhang, Jing; Ross, Mark; Ganguly, Auroop R; Nachabe, Mahmood

    2008-01-01

    Rainfall disaggregation in time can be useful for the simulation of hydrologic systems and the prediction of floods and flash floods. Disaggregation of rainfall to timescales less than 1 h can be especially useful for small urbanized watershed study, and for continuous hydrologic simulations and when Hortonian or saturation-excess runoff dominates. However, the majority of rain gauges in any region record rainfall in daily time steps or, very often, hourly records have extensive missing data. Also, the convective nature of the rainfall can result in significant differences in the measured rainfall at nearby gauges. This study evaluates several statistical approaches for rainfall disaggregation which may be applicable using data from West-Central Florida, specifically from 1 h observations to 15 min records, and proposes new methodologies that have the potential to outperform existing approaches. Four approaches are examined. The first approach is an existing direct scaling method that utilizes observed 15 min rainfall at secondary rain gauges, to disaggregate observed 1 h rainfall at more numerous primary rain gauges. The second approach is an extension of an existing method for continuous rainfall disaggregation through statistical distributional assumptions. The third approach relies on artificial neural networks for the disaggregation process without sorting and the fourth approach extends the neural network methods through statistical preprocessing via new sorting and desorting schemes. The applicability and performance of these methods were evaluated using information from a fairly dense rain gauge network in West-Central Florida. Of the four methods compared, the sorted neural networks and the direct scaling method predicted peak rainfall magnitudes significantly better than the remaining techniques. The study also suggests that desorting algorithms would also be useful to randomly replace the artificial hyetograph within a rainfall period.

  15. Statistical image reconstruction methods for simultaneous emission/transmission PET scans

    SciTech Connect

    Erdogan, H.; Fessler, J.A.

    1996-12-31

    Transmission scans are necessary for estimating the attenuation correction factors (ACFs) to yield quantitatively accurate PET emission images. To reduce the total scan time, post-injection transmission scans have been proposed in which one can simultaneously acquire emission and transmission data using rod sources and sinogram windowing. However, since the post-injection transmission scans are corrupted by emission coincidences, accurate correction for attenuation becomes more challenging. Conventional methods (emission subtraction) for ACF computation from post-injection scans are suboptimal and require relatively long scan times. We introduce statistical methods based on penalized-likelihood objectives to compute ACFs and then use them to reconstruct lower noise PET emission images from simultaneous transmission/emission scans. Simulations show the efficacy of the proposed methods. These methods improve image quality and SNR of the estimates as compared to conventional methods.

  16. Experimental studies of the properties of 'simulated' upstream turbulence using a statistical multipoint method

    NASA Technical Reports Server (NTRS)

    Orlowski, D. S.; Le, G.; Russell, C. T.; Krauss-Varban, D.; Omidi, N.

    1995-01-01

    In this report we present a different approach to the multipoint measurement of magnetic fields and plasma. This is called the multi-spacecraft ensemble technique (MET), essentially free of process restrictions, such as linearity and stationarity. We comprehensively discuss the other conditions and limitations intrinsic to this statistical method. We also show the results of the application of the ensemble method to the synthetic data obtained from a hybrid simulation in the region upstream of a quasi-parallel shock. The important implications of the above approach for the CLUSTER mission are discussed.

  17. Sharpening method of satellite thermal image based on the geographical statistical model

    NASA Astrophysics Data System (ADS)

    Qi, Pengcheng; Hu, Shixiong; Zhang, Haijun; Guo, Guangmeng

    2016-04-01

    To improve the effectiveness of thermal sharpening in mountainous regions, paying more attention to the laws of land surface energy balance, a thermal sharpening method based on the geographical statistical model (GSM) is proposed. Explanatory variables were selected from the processes of land surface energy budget and thermal infrared electromagnetic radiation transmission, then high spatial resolution (57 m) raster layers were generated for these variables through spatially simulating or using other raster data as proxies. Based on this, the local adaptation statistical relationship between brightness temperature (BT) and the explanatory variables, i.e., the GSM, was built at 1026-m resolution using the method of multivariate adaptive regression splines. Finally, the GSM was applied to the high-resolution (57-m) explanatory variables; thus, the high-resolution (57-m) BT image was obtained. This method produced a sharpening result with low error and good visual effect. The method can avoid the blind choice of explanatory variables and remove the dependence on synchronous imagery at visible and near-infrared bands. The influences of the explanatory variable combination, sampling method, and the residual error correction on sharpening results were analyzed deliberately, and their influence mechanisms are reported herein.

  18. Performance of statistical methods to correct food intake distribution: comparison between observed and estimated usual intake.

    PubMed

    Verly-Jr, Eliseu; Oliveira, Dayan C R S; Fisberg, Regina M; Marchioni, Dirce Maria L

    2016-09-01

    There are statistical methods that remove the within-person random error and estimate the usual intake when there is a second 24-h recall (24HR) for at least a subsample of the study population. We aimed to compare the distribution of usual food intake estimated by statistical models with the distribution of observed usual intake. A total of 302 individuals from Rio de Janeiro (Brazil) answered twenty, non-consecutive 24HR; the average length of follow-up was 3 months. The usual food intake was considered as the average of the 20 collection days of food intake. Using data sets with a pair of 2 collection days, usual percentiles of intake of the selected foods using two methods were estimated (National Cancer Institute (NCI) method and Multiple Source Method (MSM)). These estimates were compared with the percentiles of the observed usual intake. Selected foods comprised a range of parameter distributions: skewness, percentage of zero intakes and within- and between-person intakes. Both methods performed well but failed in some situations. In most cases, NCI and MSM produced similar percentiles between each other and values very close to the true intake, and they better represented the usual intake compared with 2-d mean. The smallest precision was observed in the upper tail of the distribution. In spite of the underestimation and overestimation of percentiles of intake, from a public health standpoint, these biases appear not to be of major concern. PMID:27523187

  19. A robust vector field correction method via a mixture statistical model of PIV signal

    NASA Astrophysics Data System (ADS)

    Lee, Yong; Yang, Hua; Yin, Zhouping

    2016-03-01

    Outlier (spurious vector) is a common problem in practical velocity field measurement using particle image velocimetry technology (PIV), and it should be validated and replaced by a reliable value. One of the most challenging problems is to correctly label the outliers under the circumstance that measurement noise exists or the flow becomes turbulent. Moreover, the outlier's cluster occurrence makes it difficult to pick out all the outliers. Most of current methods validate and correct the outliers using local statistical models in a single pass. In this work, a vector field correction (VFC) method is proposed directly from a mixture statistical model of PIV signal. Actually, this problem is formulated as a maximum a posteriori (MAP) estimation of a Bayesian model with hidden/latent variables, labeling the outliers in the original field. The solution of this MAP estimation, i.e., the outlier set and the restored flow field, is optimized iteratively using an expectation-maximization algorithm. We illustrated this VFC method on two kinds of synthetic velocity fields and two kinds of experimental data and demonstrated that it is robust to a very large number of outliers (even up to 60 %). Besides, the proposed VFC method has high accuracy and excellent compatibility for clustered outliers, compared with the state-of-the-art methods. Our VFC algorithm is computationally efficient, and corresponding Matlab code is provided for others to use it. In addition, our approach is general and can be seamlessly extended to three-dimensional-three-component (3D3C) PIV data.

  20. Integration of Remote Sensing Techniques With Statistical Methods For Landslide Monitoring and Risk Assessment

    NASA Astrophysics Data System (ADS)

    van Westen, Cees; Wunderle, Stefan; Pasquali, Paolo

    In the frame of the Date User Program 2 (DUP) of the European Space Agency (ESA) a new method will be presented to derive landslide hazards, which was developed in close co-operation with the end users in Honduras and Switzerland, respectively. The objective of thi s project is to define a sustainable service using the novel approach based on the fusion of two independent methods, namely combining differential SAR Interferometry techniques (DInSAR) with a statistical approach. The bivariate statistical analysis is based on parameter maps (slope, geomorphology, land use) derived from remote sensing data and field checks as well as on historical aerial photos. The hybrid method is based on SAR data of the last years and new ENVISAT-ASAR data as well as historical data (i.e. former landslides detected in aerial photos), respectively. The historical occurrence of landslides will be combined with actual land sliding and creeping obtained from DInSAR. The landslide occurrence map in high quality forms the input for the statistical landslide hazard analysis. The method intends to derive information on landslide hazards, preferably in the form of probabilities, which will be combined with information on building stock, infrastructure and population density. The vulnerability of population and infrastructure will be taken into account by a weighting factor. The resulting risk maps will be of great value for local authorities, Comisión Permanente de Contingencias (COPECO) of Honduras, local GIS specialists, policy makers and reinsurance companies. We will show the results of the Service Definition Project with some examples of the new method especially for Tegucigalpa the capital of Honduras with approximately 1 million inhabitants.

  1. Direct comparison of two statistical methods for determination of evoked-potential thresholds

    NASA Astrophysics Data System (ADS)

    Langford, Ted L.; Patterson, James H., Jr.

    1994-07-01

    Several statistical procedures have been proposed as objective methods for determining evoked-potential thresholds. Data have been presented to support each of the methods, but there have not been direct comparisons using the same data. The goal of the present study was to evaluate correlation and variance ratio statistics using common data. A secondary goal was to evaluate the utility of a derived potential for determining thresholds. Chronic, bipolar electrodes were stereotaxically implanted in the inferior colliculi of six chinchillas. Evoked potentials were obtained at 0.25, 0.5, 1.0, 2.0, 4.0 and 8.0 kHz using 12-ms tone bursts and 12-ms tone bursts superimposed on 120-ms pedestal tones which were of the same frequency as the bursts, but lower in amplitude by 15 dB. Alternate responses were averaged in blocks of 200 to 4000 depending on the size of the response. Correlations were calculated for the pairs of averages. A response was deemed present if the correlation coefficient reached the 0.05 level of significance in 4000 or fewer averages. Threshold was defined as the mean of the level at which the correlation was significant and a level 5 dB below that at which it was not. Variance ratios were calculated as described by Elberling and Don (1984) using the same data. Averaged tone burst and tone burst-plus pedestal data were differenced and the resulting waveforms subjected to the same statistical analyses described above. All analyses yielded thresholds which were essentially the same as those obtained using behavioral methods. When the difference between stimulus durations is taken into account, however, evoked-potential methods produced lower thresholds than behavioral methods.

  2. An Embedded Statistical Method for Coupling Molecular Dynamics and Finite Element Analyses

    NASA Technical Reports Server (NTRS)

    Saether, E.; Glaessgen, E.H.; Yamakov, V.

    2008-01-01

    The coupling of molecular dynamics (MD) simulations with finite element methods (FEM) yields computationally efficient models that link fundamental material processes at the atomistic level with continuum field responses at higher length scales. The theoretical challenge involves developing a seamless connection along an interface between two inherently different simulation frameworks. Various specialized methods have been developed to solve particular classes of problems. Many of these methods link the kinematics of individual MD atoms with FEM nodes at their common interface, necessarily requiring that the finite element mesh be refined to atomic resolution. Some of these coupling approaches also require simulations to be carried out at 0 K and restrict modeling to two-dimensional material domains due to difficulties in simulating full three-dimensional material processes. In the present work, a new approach to MD-FEM coupling is developed based on a restatement of the standard boundary value problem used to define a coupled domain. The method replaces a direct linkage of individual MD atoms and finite element (FE) nodes with a statistical averaging of atomistic displacements in local atomic volumes associated with each FE node in an interface region. The FEM and MD computational systems are effectively independent and communicate only through an iterative update of their boundary conditions. With the use of statistical averages of the atomistic quantities to couple the two computational schemes, the developed approach is referred to as an embedded statistical coupling method (ESCM). ESCM provides an enhanced coupling methodology that is inherently applicable to three-dimensional domains, avoids discretization of the continuum model to atomic scale resolution, and permits finite temperature states to be applied.

  3. The secular geomagnetic variation. Statistical methods for paleomagnetic directions in sediments

    NASA Astrophysics Data System (ADS)

    Khokhlov, A. V.

    2014-07-01

    Understanding the character of variations in the magnetic field of the Earth in the geological past requires a mathematically substantiated method for testing the statistical hypotheses against the real paleomagnetic data. As known, the paleomagnetic data from lava flows are sort of momentary snapshots of the state of the ancient magnetic field. Being quite fragmentary in time and space, these data compose what is referred to as a sample in statistics: on the close discrimination of the lava flows, the internal correlations in the data are absent. It is well known that the distributions of the paleomagnetic directions from the sedimentary data differ from the distributions in lavas, which is mainly due to the effect of averaging of the magnetization over the time interval corresponding to the accumulation of sedimentary layers represented in the rock specimen. Assuming the rate of sedimentation to be known for each specimen, one can suggest the method for the quantitative testing the statistical consistency of the paleomagnetic data in the sediments with the model variations of the magnetic field of the Earth in terms of the Giant Gaussian Process (GGP). It turned out that the averaging effect can well be allowed for by the coefficients of GGP, and the scheme of the further testing is in this case identical to the scheme of testing the paleomagnetic data obtained from lavas.

  4. Statistical Methods and Tools for Uxo Characterization (SERDP Final Technical Report)

    SciTech Connect

    Pulsipher, Brent A.; Gilbert, Richard O.; Wilson, John E.; Hassig, Nancy L.; Carlson, Deborah K.; O'Brien, Robert F.; Bates, Derrick J.; Sandness, Gerald A.; Anderson, Kevin K.

    2004-11-15

    The Strategic Environmental Research and Development Program (SERDP) issued a statement of need for FY01 titled Statistical Sampling for Unexploded Ordnance (UXO) Site Characterization that solicited proposals to develop statistically valid sampling protocols for cost-effective, practical, and reliable investigation of sites contaminated with UXO; protocols that could be validated through subsequent field demonstrations. The SERDP goal was the development of a sampling strategy for which a fraction of the site is initially surveyed by geophysical detectors to confidently identify clean areas and subsections (target areas, TAs) that had elevated densities of anomalous geophysical detector readings that could indicate the presence of UXO. More detailed surveys could then be conducted to search the identified TAs for UXO. SERDP funded three projects: those proposed by the Pacific Northwest National Laboratory (PNNL) (SERDP Project No. UXO 1199), Sandia National Laboratory (SNL), and Oak Ridge National Laboratory (ORNL). The projects were closely coordinated to minimize duplication of effort and facilitate use of shared algorithms where feasible. This final report for PNNL Project 1199 describes the methods developed by PNNL to address SERDP's statement-of-need for the development of statistically-based geophysical survey methods for sites where 100% surveys are unattainable or cost prohibitive.

  5. Statistical methods for detecting differentially abundant features in clinical metagenomic samples.

    PubMed

    White, James Robert; Nagarajan, Niranjan; Pop, Mihai

    2009-04-01

    Numerous studies are currently underway to characterize the microbial communities inhabiting our world. These studies aim to dramatically expand our understanding of the microbial biosphere and, more importantly, hope to reveal the secrets of the complex symbiotic relationship between us and our commensal bacterial microflora. An important prerequisite for such discoveries are computational tools that are able to rapidly and accurately compare large datasets generated from complex bacterial communities to identify features that distinguish them.We present a statistical method for comparing clinical metagenomic samples from two treatment populations on the basis of count data (e.g. as obtained through sequencing) to detect differentially abundant features. Our method, Metastats, employs the false discovery rate to improve specificity in high-complexity environments, and separately handles sparsely-sampled features using Fisher's exact test. Under a variety of simulations, we show that Metastats performs well compared to previously used methods, and significantly outperforms other methods for features with sparse counts. We demonstrate the utility of our method on several datasets including a 16S rRNA survey of obese and lean human gut microbiomes, COG functional profiles of infant and mature gut microbiomes, and bacterial and viral metabolic subsystem data inferred from random sequencing of 85 metagenomes. The application of our method to the obesity dataset reveals differences between obese and lean subjects not reported in the original study. For the COG and subsystem datasets, we provide the first statistically rigorous assessment of the differences between these populations. The methods described in this paper are the first to address clinical metagenomic datasets comprising samples from multiple subjects. Our methods are robust across datasets of varied complexity and sampling level. While designed for metagenomic applications, our software can also be applied

  6. Boosting Bayesian parameter inference of stochastic differential equation models with methods from statistical physics

    NASA Astrophysics Data System (ADS)

    Albert, Carlo; Ulzega, Simone; Stoop, Ruedi

    2016-04-01

    Measured time-series of both precipitation and runoff are known to exhibit highly non-trivial statistical properties. For making reliable probabilistic predictions in hydrology, it is therefore desirable to have stochastic models with output distributions that share these properties. When parameters of such models have to be inferred from data, we also need to quantify the associated parametric uncertainty. For non-trivial stochastic models, however, this latter step is typically very demanding, both conceptually and numerically, and always never done in hydrology. Here, we demonstrate that methods developed in statistical physics make a large class of stochastic differential equation (SDE) models amenable to a full-fledged Bayesian parameter inference. For concreteness we demonstrate these methods by means of a simple yet non-trivial toy SDE model. We consider a natural catchment that can be described by a linear reservoir, at the scale of observation. All the neglected processes are assumed to happen at much shorter time-scales and are therefore modeled with a Gaussian white noise term, the standard deviation of which is assumed to scale linearly with the system state (water volume in the catchment). Even for constant input, the outputs of this simple non-linear SDE model show a wealth of desirable statistical properties, such as fat-tailed distributions and long-range correlations. Standard algorithms for Bayesian inference fail, for models of this kind, because their likelihood functions are extremely high-dimensional intractable integrals over all possible model realizations. The use of Kalman filters is illegitimate due to the non-linearity of the model. Particle filters could be used but become increasingly inefficient with growing number of data points. Hamiltonian Monte Carlo algorithms allow us to translate this inference problem to the problem of simulating the dynamics of a statistical mechanics system and give us access to most sophisticated methods

  7. Application of the non-equilibrium statistical operator method (NESOM) to dissipation atomic force microscopy

    NASA Astrophysics Data System (ADS)

    Mo, M. Y.; Kantorovich, L.

    2001-02-01

    We apply the non-equilibrium statistical operator method to non-contact atomic force microscopy, considering explicitly the statistical effects of (classical) vibrations of surface atoms and associated energy transfer from the tip to the surface. We derive several, physically and mathematically equivalent, forms of the equation of motion for the tip, each containing a friction term due to the so-called intrinsic mechanism of energy dissipation first suggested by Gauthier and Tsukada. Our exact treatment supports the results of some earlier work which were all approximate. We also demonstrate, using the same theory, that the distribution function of the tip in the coordinate-momentum phase subspace is governed by the Fokker-Planck equation and should be considered as strongly peaked around the exact values t and t of the momentum and the position of the tip, respectively.

  8. Advanced statistical methods for improved data analysis of NASA astrophysics missions

    NASA Technical Reports Server (NTRS)

    Feigelson, Eric D.

    1992-01-01

    The investigators under this grant studied ways to improve the statistical analysis of astronomical data. They looked at existing techniques, the development of new techniques, and the production and distribution of specialized software to the astronomical community. Abstracts of nine papers that were produced are included, as well as brief descriptions of four software packages. The articles that are abstracted discuss analytical and Monte Carlo comparisons of six different linear least squares fits, a (second) paper on linear regression in astronomy, two reviews of public domain software for the astronomer, subsample and half-sample methods for estimating sampling distributions, a nonparametric estimation of survival functions under dependent competing risks, censoring in astronomical data due to nondetections, an astronomy survival analysis computer package called ASURV, and improving the statistical methodology of astronomical data analysis.

  9. Effect Size as the Essential Statistic in Developing Methods for mTBI Diagnosis

    PubMed Central

    Gibson, Douglas Brandt

    2015-01-01

    The descriptive statistic known as “effect size” measures the distinguishability of two sets of data. Distingishability is at the core of diagnosis. This article is intended to point out the importance of effect size in the development of effective diagnostics for mild traumatic brain injury and to point out the applicability of the effect size statistic in comparing diagnostic efficiency across the main proposed TBI diagnostic methods: psychological, physiological, biochemical, and radiologic. Comparing diagnostic approaches is difficult because different researcher in different fields have different approaches to measuring efficacy. Converting diverse measures to effect sizes, as is done in meta-analysis, is a relatively easy way to make studies comparable. PMID:26150801

  10. Recognizing and analyzing variability in amyloid formation kinetics: Simulation and statistical methods.

    PubMed

    Hall, Damien; Zhao, Ran; So, Masatomo; Adachi, Masayuki; Rivas, Germán; Carver, John A; Goto, Yuji

    2016-10-01

    We examine the phenomenon of variability in the kinetics of amyloid formation and detail methods for its simulation, identification and analysis. Simulated data, reflecting intrinsic variability, were produced using rate constants, randomly sampled from a pre-defined distribution, as parameters in an irreversible nucleation-growth kinetic model. Simulated kinetic traces were reduced in complexity through description in terms of three characteristic parameters. Practical methods for assessing convergence of the reduced parameter distributions were introduced and a bootstrap procedure was applied to determine convergence for different levels of intrinsic variation. Statistical methods for assessing the significance of shifts in parameter distributions, relating to either change in parameter mean or distribution shape, were tested. Robust methods for analyzing and interpreting kinetic data possessing significant intrinsic variance will allow greater scrutiny of the effects of anti-amyloid compounds in drug trials. PMID:27430932

  11. Addressing impacts of different statistical downscaling methods on large scale hydrologic simulations

    NASA Astrophysics Data System (ADS)

    Mizukami, N.; Clark, M. P.; Gutmann, E. D.; Mendoza, P. A.; Brekke, L. D.; Arnold, J.; Raff, D. A.

    2013-12-01

    Many hydrologic assessments, such as evaluations of climate change impacts on water resources, require downscaled climate model outputs to force hydrologic simulations at a spatial resolution finer than the climate models' native scale. Statistical downscaling is an attractive alternative to dynamical downscaling methods for continental scale hydrologic applications because of its lower computational cost. The goal of this study is to illustrate and compare how the errors in precipitation and temperature produced by different statistical downscaling methods propagate into hydrologic simulations. Multi-decadal hydrologic simulations were performed with three process-based hydrologic models (CLM, VIC, and PRMS) forced by multiple climate datasets over the contiguous United States. The forcing datasets include climate data derived from gauge observations (M02) as well as climate data downscaled from the NCEP-NCAR reanalysis using 4 statistical downscaling methods for a domain with 12-km grid spacing: two forms of Bias Corrected Spatially Disaggregated methods (BCSD-monthly and BCSD-daily), Bias Corrected Constructed Analogue (BCCA), and Asynchronous Regression (AR). Our results show that both BCCA and BCSD-daily underestimate extreme precipitation events while AR produces these correctly at the scale at which the simulations were run but does not scale them up appropriately to larger basin scales like HUC-4 and HUC-2. These artifacts lead to a poor representation of flooding events when hydrologic models are forced by these methods over a range of spatial scales. We also illustrate that errors in precipitation depths dominate impacts on runoff depth estimations, and that errors in wet day frequency have a larger effect on shortwave radiation estimations than do the errors in temperatures; this error subsequently affects the partitioning of precipitation into evaporation and runoff as we show over mountainous areas of the upper Colorado River. Finally we show the inter

  12. Statistical Methods and Software for the Analysis of Occupational Exposure Data with Non-detectable Values

    SciTech Connect

    Frome, EL

    2005-09-20

    Environmental exposure measurements are, in general, positive and may be subject to left censoring; i.e,. the measured value is less than a ''detection limit''. In occupational monitoring, strategies for assessing workplace exposures typically focus on the mean exposure level or the probability that any measurement exceeds a limit. Parametric methods used to determine acceptable levels of exposure, are often based on a two parameter lognormal distribution. The mean exposure level, an upper percentile, and the exceedance fraction are used to characterize exposure levels, and confidence limits are used to describe the uncertainty in these estimates. Statistical methods for random samples (without non-detects) from the lognormal distribution are well known for each of these situations. In this report, methods for estimating these quantities based on the maximum likelihood method for randomly left censored lognormal data are described and graphical methods are used to evaluate the lognormal assumption. If the lognormal model is in doubt and an alternative distribution for the exposure profile of a similar exposure group is not available, then nonparametric methods for left censored data are used. The mean exposure level, along with the upper confidence limit, is obtained using the product limit estimate, and the upper confidence limit on an upper percentile (i.e., the upper tolerance limit) is obtained using a nonparametric approach. All of these methods are well known but computational complexity has limited their use in routine data analysis with left censored data. The recent development of the R environment for statistical data analysis and graphics has greatly enhanced the availability of high-quality nonproprietary (open source) software that serves as the basis for implementing the methods in this paper.

  13. Introducing 3D U-statistic method for separating anomaly from background in exploration geochemical data with associated software development

    NASA Astrophysics Data System (ADS)

    Ghannadpour, Seyyed Saeed; Hezarkhani, Ardeshir

    2016-03-01

    The U-statistic method is one of the most important structural methods to separate the anomaly from the background. It considers the location of samples and carries out the statistical analysis of the data without judging from a geochemical point of view and tries to separate subpopulations and determine anomalous areas. In the present study, to use U-statistic method in three-dimensional (3D) condition, U-statistic is applied on the grade of two ideal test examples, by considering sample Z values (elevation). So far, this is the first time that this method has been applied on a 3D condition. To evaluate the performance of 3D U-statistic method and in order to compare U-statistic with one non-structural method, the method of threshold assessment based on median and standard deviation (MSD method) is applied on the two example tests. Results show that the samples indicated by U-statistic method as anomalous are more regular and involve less dispersion than those indicated by the MSD method. So that, according to the location of anomalous samples, denser areas of them can be determined as promising zones. Moreover, results show that at a threshold of U = 0, the total error of misclassification for U-statistic method is much smaller than the total error of criteria of bar {x}+n× s. Finally, 3D model of two test examples for separating anomaly from background using 3D U-statistic method is provided. The source code for a software program, which was developed in the MATLAB programming language in order to perform the calculations of the 3D U-spatial statistic method, is additionally provided. This software is compatible with all the geochemical varieties and can be used in similar exploration projects.

  14. Combined Bayesian statistics and load duration curve method for bacteria nonpoint source loading estimation.

    PubMed

    Shen, Jian; Zhao, Yuan

    2010-01-01

    Nonpoint source load estimation is an essential part of the development of the bacterial total maximum daily load (TMDL) mandated by the Clean Water Act. However, the currently widely used watershed-receiving water modeling approach is usually associated with a high level of uncertainty and requires long-term observational data and intensive training effort. The load duration curve (LDC) method recommended by the EPA provides a simpler way to estimate bacteria loading. This method, however, does not take into consideration the specific fate and transport mechanisms of the pollutant and cannot address the uncertainty. In this study, a Bayesian statistical approach is applied to the Escherichia coli TMDL development of a stream on the Eastern Shore of Virginia to inversely estimate watershed bacteria loads from the in-stream monitoring data. The mechanism of bacteria transport is incorporated. The effects of temperature, bottom slope, and flow on allowable and existing load calculations are discussed. The uncertainties associated with load estimation are also fully described. Our method combines the merits of LDC, mechanistic modeling, and Bayesian statistics, while overcoming some of the shortcomings associated with these methods. It is a cost-effective tool for bacteria TMDL development and can be modified and applied to multi-segment streams as well. PMID:19781737

  15. Monitoring Method of Cow Anthrax Based on Gis and Spatial Statistical Analysis

    NASA Astrophysics Data System (ADS)

    Li, Lin; Yang, Yong; Wang, Hongbin; Dong, Jing; Zhao, Yujun; He, Jianbin; Fan, Honggang

    Geographic information system (GIS) is a computer application system, which possesses the ability of manipulating spatial information and has been used in many fields related with the spatial information management. Many methods and models have been established for analyzing animal diseases distribution models and temporal-spatial transmission models. Great benefits have been gained from the application of GIS in animal disease epidemiology. GIS is now a very important tool in animal disease epidemiological research. Spatial analysis function of GIS can be widened and strengthened by using spatial statistical analysis, allowing for the deeper exploration, analysis, manipulation and interpretation of spatial pattern and spatial correlation of the animal disease. In this paper, we analyzed the cow anthrax spatial distribution characteristics in the target district A (due to the secret of epidemic data we call it district A) based on the established GIS of the cow anthrax in this district in combination of spatial statistical analysis and GIS. The Cow anthrax is biogeochemical disease, and its geographical distribution is related closely to the environmental factors of habitats and has some spatial characteristics, and therefore the correct analysis of the spatial distribution of anthrax cow for monitoring and the prevention and control of anthrax has a very important role. However, the application of classic statistical methods in some areas is very difficult because of the pastoral nomadic context. The high mobility of livestock and the lack of enough suitable sampling for the some of the difficulties in monitoring currently make it nearly impossible to apply rigorous random sampling methods. It is thus necessary to develop an alternative sampling method, which could overcome the lack of sampling and meet the requirements for randomness. The GIS computer application software ArcGIS9.1 was used to overcome the lack of data of sampling sites.Using ArcGIS 9.1 and GEODA

  16. InSAR Tropospheric Correction Methods: A Statistical Comparison over Different Regions

    NASA Astrophysics Data System (ADS)

    Bekaert, D. P.; Walters, R. J.; Wright, T. J.; Hooper, A. J.; Parker, D. J.

    2015-12-01

    Observing small magnitude surface displacements through InSAR is highly challenging, and requires advanced correction techniques to reduce noise. In fact, one of the largest obstacles facing the InSAR community is related to tropospheric noise correction. Spatial and temporal variations in temperature, pressure, and relative humidity result in a spatially-variable InSAR tropospheric signal, which masks smaller surface displacements due to tectonic or volcanic deformation. Correction methods applied today include those relying on weather model data, GNSS and/or spectrometer data. Unfortunately, these methods are often limited by the spatial and temporal resolution of the auxiliary data. Alternatively a correction can be estimated from the high-resolution interferometric phase by assuming a linear or a power-law relationship between the phase and topography. For these methods, the challenge lies in separating deformation from tropospheric signals. We will present results of a statistical comparison of the state-of-the-art tropospheric corrections estimated from spectrometer products (MERIS and MODIS), a low and high spatial-resolution weather model (ERA-I and WRF), and both the conventional linear and power-law empirical methods. We evaluate the correction capability over Southern Mexico, Italy, and El Hierro, and investigate the impact of increasing cloud cover on the accuracy of the tropospheric delay estimation. We find that each method has its strengths and weaknesses, and suggest that further developments should aim to combine different correction methods. All the presented methods are included into our new open source software package called TRAIN - Toolbox for Reducing Atmospheric InSAR Noise (Bekaert et al., in review), which is available to the community Bekaert, D., R. Walters, T. Wright, A. Hooper, and D. Parker (in review), Statistical comparison of InSAR tropospheric correction techniques, Remote Sensing of Environment

  17. Inter-comparison of statistical downscaling methods for projection of extreme precipitation in Europe

    NASA Astrophysics Data System (ADS)

    Sunyer, M. A.; Hundecha, Y.; Lawrence, D.; Madsen, H.; Willems, P.; Martinkova, M.; Vormoor, K.; Bürger, G.; Hanel, M.; Kriaučiūnienė, J.; Loukas, A.; Osuch, M.; Yücel, I.

    2015-04-01

    Information on extreme precipitation for future climate is needed to assess the changes in the frequency and intensity of flooding. The primary source of information in climate change impact studies is climate model projections. However, due to the coarse resolution and biases of these models, they cannot be directly used in hydrological models. Hence, statistical downscaling is necessary to address climate change impacts at the catchment scale. This study compares eight statistical downscaling methods (SDMs) often used in climate change impact studies. Four methods are based on change factors (CFs), three are bias correction (BC) methods, and one is a perfect prognosis method. The eight methods are used to downscale precipitation output from 15 regional climate models (RCMs) from the ENSEMBLES project for 11 catchments in Europe. The overall results point to an increase in extreme precipitation in most catchments in both winter and summer. For individual catchments, the downscaled time series tend to agree on the direction of the change but differ in the magnitude. Differences between the SDMs vary between the catchments and depend on the season analysed. Similarly, general conclusions cannot be drawn regarding the differences between CFs and BC methods. The performance of the BC methods during the control period also depends on the catchment, but in most cases they represent an improvement compared to RCM outputs. Analysis of the variance in the ensemble of RCMs and SDMs indicates that at least 30% and up to approximately half of the total variance is derived from the SDMs. This study illustrates the large variability in the expected changes in extreme precipitation and highlights the need for considering an ensemble of both SDMs and climate models. Recommendations are provided for the selection of the most suitable SDMs to include in the analysis.

  18. An Analysis of Research Methods and Statistical Techniques Used by Doctoral Dissertation at the Education Sciences in Turkey

    ERIC Educational Resources Information Center

    Karadag, Engin

    2010-01-01

    To assess research methods and analysis of statistical techniques employed by educational researchers, this study surveyed unpublished doctoral dissertation from 2003 to 2007. Frequently used research methods consisted of experimental research; a survey; a correlational study; and a case study. Descriptive statistics, t-test, ANOVA, factor…

  19. University and Student Segmentation: Multilevel Latent-Class Analysis of Students' Attitudes towards Research Methods and Statistics

    ERIC Educational Resources Information Center

    Mutz, Rudiger; Daniel, Hans-Dieter

    2013-01-01

    Background: It is often claimed that psychology students' attitudes towards research methods and statistics affect course enrolment, persistence, achievement, and course climate. However, the inter-institutional variability has been widely neglected in the research on students' attitudes towards research methods and statistics, but it is important…

  20. Appplication of statistical mechanical methods to the modeling of social networks

    NASA Astrophysics Data System (ADS)

    Strathman, Anthony Robert

    With the recent availability of large-scale social data sets, social networks have become open to quantitative analysis via the methods of statistical physics. We examine the statistical properties of a real large-scale social network, generated from cellular phone call-trace logs. We find this network, like many other social networks to be assortative (r = 0.31) and clustered (i.e., strongly transitive, C = 0.21). We measure fluctuation scaling to identify the presence of internal structure in the network and find that structural inhomogeneity effectively disappears at the scale of a few hundred nodes, though there is no sharp cutoff. We introduce an agent-based model of social behavior, designed to model the formation and dissolution of social ties. The model is a modified Metropolis algorithm containing agents operating under the basic sociological constraints of reciprocity, communication need and transitivity. The model introduces the concept of a social temperature. We go on to show that this simple model reproduces the global statistical network features (incl. assortativity, connected fraction, mean degree, clustering, and mean shortest path length) of the real network data and undergoes two phase transitions, one being from a "gas" to a "liquid" state and the second from a liquid to a glassy state as function of this social temperature.

  1. Integrating statistical genetic and geospatial methods brings new power to phylogeography.

    PubMed

    Chan, Lauren M; Brown, Jason L; Yoder, Anne D

    2011-05-01

    The field of phylogeography continues to grow in terms of power and accessibility. Initially uniting population genetics and phylogenetics, it now spans disciplines as diverse as geology, statistics, climatology, ecology, physiology, and bioinformatics to name a few. One major and recent integration driving the field forward is between "statistical phylogeography" and Geographic Information Systems (GIS) (Knowles, 2009). Merging genetic and geospatial data, and their associated methodological toolkits, is helping to bring explicit hypothesis testing to the field of phylogeography. Hypotheses derived from one approach can be reciprocally tested with data derived from the other field and the synthesis of these data can help place demographic events in an historical and spatial context, guide genetic sampling, and point to areas for further investigation. Here, we present three practical examples of empirical analysis that integrate statistical genetic and GIS tools to construct and test phylogeographic hypotheses. Insights into the evolutionary mechanisms underlying recent divergences can benefit from simultaneously considering diverse types of information to iteratively test and reformulate hypotheses. Our goal is to provide the reader with an introduction to the variety of available tools and their potential application to typical questions in phylogeography with the hope that integrative methods will be more broadly and commonly applied to other biological systems and data sets. PMID:21352934

  2. New Statistical Methods for the Analysis of the Cratering on Venus

    NASA Astrophysics Data System (ADS)

    Xie, M.; Smrekar, S. E.; Handcock, M. S.

    2014-12-01

    The sparse crater population (~1000 craters) on Venus is the most important clue of determining the planet's surface age and aids in understanding its geologic history. What processes (volcanism, tectonism, weathering, etc.) modify the total impact crater population? Are the processes regional or global in occurrence? The heated debate on these questions points to the need for better approaches. We present new statistical methods for the analysis of the crater locations and characteristics. Specifically: 1) We produce a map of crater density and the proportion of no halo craters (inferred to be modified) by using generalized additive models, and smoothing splines with a spherical spline basis set. Based on this map, we are able to predict the probability of a crater has no halo given that there is a crater at that point. We also obtain a continuous representation of the ratio of craters with no halo as a function of crater density. This approach allows us to look for regions that appear to have experienced more or less modification, and are thus potentially older or younger. 2) We examine the randomness or clustering of distributions of craters by type (e.g. dark floored, intermediate). For example, for dark floored craters we consider two hypotheses: i) the dark floored craters are randomly distributed on the surface; ii) the dark floored craters are random given the locations of the crater population. Instead of only using a single measure such as average nearest neighbor distance, we use the probability density function of these distances, and compare it to complete spatial randomness to get the relative probability density function. This function gives us a clearer picture of how and where the nearest neighbor distances differ from complete spatial randomness. We also conduct statistical tests of these hypotheses. Confidence intervals with specified global coverage are constructed. Software to reproduce the methods is available in the open source statistics

  3. Wastewater-Based Epidemiology of Stimulant Drugs: Functional Data Analysis Compared to Traditional Statistical Methods

    PubMed Central

    Salvatore, Stefania; Bramness, Jørgen Gustav; Reid, Malcolm J.; Thomas, Kevin Victor; Harman, Christopher; Røislien, Jo

    2015-01-01

    Background Wastewater-based epidemiology (WBE) is a new methodology for estimating the drug load in a population. Simple summary statistics and specification tests have typically been used to analyze WBE data, comparing differences between weekday and weekend loads. Such standard statistical methods may, however, overlook important nuanced information in the data. In this study, we apply functional data analysis (FDA) to WBE data and compare the results to those obtained from more traditional summary measures. Methods We analysed temporal WBE data from 42 European cities, using sewage samples collected daily for one week in March 2013. For each city, the main temporal features of two selected drugs were extracted using functional principal component (FPC) analysis, along with simpler measures such as the area under the curve (AUC). The individual cities’ scores on each of the temporal FPCs were then used as outcome variables in multiple linear regression analysis with various city and country characteristics as predictors. The results were compared to those of functional analysis of variance (FANOVA). Results The three first FPCs explained more than 99% of the temporal variation. The first component (FPC1) represented the level of the drug load, while the second and third temporal components represented the level and the timing of a weekend peak. AUC was highly correlated with FPC1, but other temporal characteristic were not captured by the simple summary measures. FANOVA was less flexible than the FPCA-based regression, and even showed concordance results. Geographical location was the main predictor for the general level of the drug load. Conclusion FDA of WBE data extracts more detailed information about drug load patterns during the week which are not identified by more traditional statistical methods. Results also suggest that regression based on FPC results is a valuable addition to FANOVA for estimating associations between temporal patterns and covariate

  4. Evaluation of Fuzzy-Logic Framework for Spatial Statistics Preserving Methods for Estimation of Missing Precipitation Data

    NASA Astrophysics Data System (ADS)

    El Sharif, H.; Teegavarapu, R. S.

    2012-12-01

    Spatial interpolation methods used for estimation of missing precipitation data at a site seldom check for their ability to preserve site and regional statistics. Such statistics are primarily defined by spatial correlations and other site-to-site statistics in a region. Preservation of site and regional statistics represents a means of assessing the validity of missing precipitation estimates at a site. This study evaluates the efficacy of a fuzzy-logic methodology for infilling missing historical daily precipitation data in preserving site and regional statistics. Rain gauge sites in the state of Kentucky, USA, are used as a case study for evaluation of this newly proposed method in comparison to traditional data infilling techniques. Several error and performance measures will be used to evaluate the methods and trade-offs in accuracy of estimation and preservation of site and regional statistics.

  5. Methods for Measurement and Statistical Analysis of the Frangibility of Strengthened Glass

    NASA Astrophysics Data System (ADS)

    Tang, Zhongzhi; Mauro, Yihong; Gee, Christopher; Duffy, Delena; Meyer, Timothy; Abrams, Matthew; Walker, Kimberly; Mauro, John

    2015-06-01

    Chemically strengthened glass features a surface compression and a balancing central tension (CT) in the interior of the glass. A greater CT is usually associated with a higher level of stored elastic energy in the glass. During a fracture event, release of a greater amount of stored energy can lead to frangibility, i.e., shorter crack branching distances, smaller fragment size, and ejection of small fragments from the glass. In this paper, the frangibility and fragmentation behaviors of a series of chemically strengthened glass samples are studied using two different manual testing methods and an automated tester. Both immediate and delayed fracture events were observed. A statistical method is proposed to determine the probability of frangible fracture for glasses ion exchanged under a specific set of conditions, and analysis is performed to understand the dependence of frangibility probability on sample thickness, CT, and testing method. We also propose a more rigorous set of criteria for qualifying frangibility.

  6. Enhancing image watermarking methods with/without reference images by optimization on second-order statistics.

    PubMed

    Tzeng, Jengnan; Hwang, Wen-Liang; Chern, I-Liang

    2002-01-01

    The watermarking method has emerged as an important tool for content tracing, authentication, and data hiding in multimedia applications. We propose a watermarking strategy in which the watermark of a host is selected from the robust features of the estimated forged images of the host. The forged images are obtained from Monte Carlo simulations of potential pirate attacks on the host image. The solution of applying an optimization technique to the second-order statistics of the features of the forged images gives two orthogonal spaces. One of them characterizes most of the variations in the modifications of the host. Our watermark is embedded in the other space that most potential pirate attacks do not touch. Thus, the embedded watermark is robust. Our watermarking method uses the same framework for watermark detection with a reference and blind detection. We demonstrate the performance of our method under various levels of attacks. PMID:18244673

  7. Comparison of classical statistical methods and artificial neural network in traffic noise prediction

    SciTech Connect

    Nedic, Vladimir; Despotovic, Danijela; Cvetanovic, Slobodan; Despotovic, Milan; Babic, Sasa

    2014-11-15

    Traffic is the main source of noise in urban environments and significantly affects human mental and physical health and labor productivity. Therefore it is very important to model the noise produced by various vehicles. Techniques for traffic noise prediction are mainly based on regression analysis, which generally is not good enough to describe the trends of noise. In this paper the application of artificial neural networks (ANNs) for the prediction of traffic noise is presented. As input variables of the neural network, the proposed structure of the traffic flow and the average speed of the traffic flow are chosen. The output variable of the network is the equivalent noise level in the given time period L{sub eq}. Based on these parameters, the network is modeled, trained and tested through a comparative analysis of the calculated values and measured levels of traffic noise using the originally developed user friendly software package. It is shown that the artificial neural networks can be a useful tool for the prediction of noise with sufficient accuracy. In addition, the measured values were also used to calculate equivalent noise level by means of classical methods, and comparative analysis is given. The results clearly show that ANN approach is superior in traffic noise level prediction to any other statistical method. - Highlights: • We proposed an ANN model for prediction of traffic noise. • We developed originally designed user friendly software package. • The results are compared with classical statistical methods. • The results are much better predictive capabilities of ANN model.

  8. Intelligent Condition Diagnosis Method Based on Adaptive Statistic Test Filter and Diagnostic Bayesian Network

    PubMed Central

    Li, Ke; Zhang, Qiuju; Wang, Kun; Chen, Peng; Wang, Huaqing

    2016-01-01

    A new fault diagnosis method for rotating machinery based on adaptive statistic test filter (ASTF) and Diagnostic Bayesian Network (DBN) is presented in this paper. ASTF is proposed to obtain weak fault features under background noise, ASTF is based on statistic hypothesis testing in the frequency domain to evaluate similarity between reference signal (noise signal) and original signal, and remove the component of high similarity. The optimal level of significance α is obtained using particle swarm optimization (PSO). To evaluate the performance of the ASTF, evaluation factor Ipq is also defined. In addition, a simulation experiment is designed to verify the effectiveness and robustness of ASTF. A sensitive evaluation method using principal component analysis (PCA) is proposed to evaluate the sensitiveness of symptom parameters (SPs) for condition diagnosis. By this way, the good SPs that have high sensitiveness for condition diagnosis can be selected. A three-layer DBN is developed to identify condition of rotation machinery based on the Bayesian Belief Network (BBN) theory. Condition diagnosis experiment for rolling element bearings demonstrates the effectiveness of the proposed method. PMID:26761006

  9. A statistical method for lung tumor segmentation uncertainty in PET images based on user inference.

    PubMed

    Zheng, Chaojie; Wang, Xiuying; Feng, Dagan

    2015-01-01

    PET has been widely accepted as an effective imaging modality for lung tumor diagnosis and treatment. However, standard criteria for delineating tumor boundary from PET are yet to develop largely due to relatively low quality of PET images, uncertain tumor boundary definition, and variety of tumor characteristics. In this paper, we propose a statistical solution to segmentation uncertainty on the basis of user inference. We firstly define the uncertainty segmentation band on the basis of segmentation probability map constructed from Random Walks (RW) algorithm; and then based on the extracted features of the user inference, we use Principle Component Analysis (PCA) to formulate the statistical model for labeling the uncertainty band. We validated our method on 10 lung PET-CT phantom studies from the public RIDER collections [1] and 16 clinical PET studies where tumors were manually delineated by two experienced radiologists. The methods were validated using Dice similarity coefficient (DSC) to measure the spatial volume overlap. Our method achieved an average DSC of 0.878 ± 0.078 on phantom studies and 0.835 ± 0.039 on clinical studies. PMID:26736741

  10. Estimation of anthropogenic heat emission over South Korea using a statistical regression method

    NASA Astrophysics Data System (ADS)

    Lee, Sang-Hyun; Kim, Soon-Tae

    2015-05-01

    Anthropogenic heating by human activity is one of the key contributing factors in forming urban heat islands, thus inclusion of the heat source plays an important role in urban meteorological and environmental modeling. In this study, gridded anthropogenic heat flux (AHF) with high spatial (1-km) and temporal (1-hr) resolution is estimated for the whole South Korea region in year 2010 using a statistical regression method which derives based on similarity of anthropogenic air pollutant emissions and AHF in their emission inventories. The bottom-up anthropogenic pollutant emissions required for the regression method are produced using the intensive Korean air pollutants emission inventories. The calculated regression-based AHF compares well with the inventory-based AHF estimation for the Gyeong-In region, demonstrating that the statistical regression method can reasonably represent spatio-temporal variation of the AHF within the region. The estimated AHF shows that for major Korean cities (Seoul, Busan, Daegu, Gwangju, Daejeon, and Ulsan) the annual mean AHF range 10-50 Wm-2 on a grid scale and 20-30W m-2 on a city-scale. The winter AHF are larger by about 22% than that in summer, while the weekday AHF are larger by 4-5% than the weekend AHF in the major Korean cities. The gridded AHF data estimated in this study can be used in mesoscale meteorological and environmental modeling for the South Korea region.

  11. Computational Performance and Statistical Accuracy of *BEAST and Comparisons with Other Methods.

    PubMed

    Ogilvie, Huw A; Heled, Joseph; Xie, Dong; Drummond, Alexei J

    2016-05-01

    Under the multispecies coalescent model of molecular evolution, gene trees have independent evolutionary histories within a shared species tree. In comparison, supermatrix concatenation methods assume that gene trees share a single common genealogical history, thereby equating gene coalescence with species divergence. The multispecies coalescent is supported by previous studies which found that its predicted distributions fit empirical data, and that concatenation is not a consistent estimator of the species tree. *BEAST, a fully Bayesian implementation of the multispecies coalescent, is popular but computationally intensive, so the increasing size of phylogenetic data sets is both a computational challenge and an opportunity for better systematics. Using simulation studies, we characterize the scaling behavior of *BEAST, and enable quantitative prediction of the impact increasing the number of loci has on both computational performance and statistical accuracy. Follow-up simulations over a wide range of parameters show that the statistical performance of *BEAST relative to concatenation improves both as branch length is reduced and as the number of loci is increased. Finally, using simulations based on estimated parameters from two phylogenomic data sets, we compare the performance of a range of species tree and concatenation methods to show that using *BEAST with tens of loci can be preferable to using concatenation with thousands of loci. Our results provide insight into the practicalities of Bayesian species tree estimation, the number of loci required to obtain a given level of accuracy and the situations in which supermatrix or summary methods will be outperformed by the fully Bayesian multispecies coalescent. PMID:26821913

  12. Computational Performance and Statistical Accuracy of *BEAST and Comparisons with Other Methods

    PubMed Central

    Ogilvie, Huw A.; Heled, Joseph; Xie, Dong; Drummond, Alexei J.

    2016-01-01

    Under the multispecies coalescent model of molecular evolution, gene trees have independent evolutionary histories within a shared species tree. In comparison, supermatrix concatenation methods assume that gene trees share a single common genealogical history, thereby equating gene coalescence with species divergence. The multispecies coalescent is supported by previous studies which found that its predicted distributions fit empirical data, and that concatenation is not a consistent estimator of the species tree. *BEAST, a fully Bayesian implementation of the multispecies coalescent, is popular but computationally intensive, so the increasing size of phylogenetic data sets is both a computational challenge and an opportunity for better systematics. Using simulation studies, we characterize the scaling behavior of *BEAST, and enable quantitative prediction of the impact increasing the number of loci has on both computational performance and statistical accuracy. Follow-up simulations over a wide range of parameters show that the statistical performance of *BEAST relative to concatenation improves both as branch length is reduced and as the number of loci is increased. Finally, using simulations based on estimated parameters from two phylogenomic data sets, we compare the performance of a range of species tree and concatenation methods to show that using *BEAST with tens of loci can be preferable to using concatenation with thousands of loci. Our results provide insight into the practicalities of Bayesian species tree estimation, the number of loci required to obtain a given level of accuracy and the situations in which supermatrix or summary methods will be outperformed by the fully Bayesian multispecies coalescent. PMID:26821913

  13. Intelligent Condition Diagnosis Method Based on Adaptive Statistic Test Filter and Diagnostic Bayesian Network.

    PubMed

    Li, Ke; Zhang, Qiuju; Wang, Kun; Chen, Peng; Wang, Huaqing

    2016-01-01

    A new fault diagnosis method for rotating machinery based on adaptive statistic test filter (ASTF) and Diagnostic Bayesian Network (DBN) is presented in this paper. ASTF is proposed to obtain weak fault features under background noise, ASTF is based on statistic hypothesis testing in the frequency domain to evaluate similarity between reference signal (noise signal) and original signal, and remove the component of high similarity. The optimal level of significance α is obtained using particle swarm optimization (PSO). To evaluate the performance of the ASTF, evaluation factor Ipq is also defined. In addition, a simulation experiment is designed to verify the effectiveness and robustness of ASTF. A sensitive evaluation method using principal component analysis (PCA) is proposed to evaluate the sensitiveness of symptom parameters (SPs) for condition diagnosis. By this way, the good SPs that have high sensitiveness for condition diagnosis can be selected. A three-layer DBN is developed to identify condition of rotation machinery based on the Bayesian Belief Network (BBN) theory. Condition diagnosis experiment for rolling element bearings demonstrates the effectiveness of the proposed method. PMID:26761006

  14. A shortcut through the Coulomb gas method for spectral linear statistics on random matrices

    NASA Astrophysics Data System (ADS)

    Deelan Cunden, Fabio; Facchi, Paolo; Vivo, Pierpaolo

    2016-04-01

    In the last decade, spectral linear statistics on large dimensional random matrices have attracted significant attention. Within the physics community, a privileged role has been played by invariant matrix ensembles for which a two-dimensional Coulomb gas analogy is available. We present a critical revision of the Coulomb gas method in random matrix theory (RMT) borrowing language and tools from large deviations theory. This allows us to formalize an equivalent, but more effective and quicker route toward RMT free energy calculations. Moreover, we argue that this more modern viewpoint is likely to shed further light on the interesting issues of weak phase transitions and evaporation phenomena recently observed in RMT.

  15. Typical Behavior of the Linear Programming Method for Combinatorial Optimization Problems: A Statistical-Mechanical Perspective

    NASA Astrophysics Data System (ADS)

    Takabe, Satoshi; Hukushima, Koji

    2014-04-01

    The typical behavior of the linear programming (LP) problem is studied as a relaxation of the minimum vertex cover problem, which is a type of integer programming (IP) problem. To deal with LP and IP using statistical mechanics, a lattice-gas model on the Erdös-Rényi random graphs is analyzed by a replica method. It is found that the LP optimal solution is typically equal to that given by IP below the critical average degree c*=e in the thermodynamic limit. The critical threshold for LP = IP extends the previous result c = 1, and coincides with the replica symmetry-breaking threshold of the IP.

  16. Comparison of statistical methods for assessment of population genetic diversity by DNA fingerprinting

    SciTech Connect

    Leonard, T.; Roth, A.; Gordon, D.; Wessendarp, T.; Smith, M.K.; Silbiger, R.; Torsella, J.

    1995-12-31

    The advent of newer techniques for genomic characterization, e.g., Random Amplified Polymorphic DNA (RAPD) fingerprinting, has motivated development of a number of statistical approaches for creating hypothesis tests using this genetic information. The authors specific interest is methods for deriving relative genetic diversity measures of feral populations subjected to varying degrees of environmental impacts. Decreased polymorphism and loss of alleles have been documented in stressed populations of some species as assayed by allozyme analysis and, more recently, by DNA fingerprinting. Multilocus fingerprinting techniques (such as RAPDS) differ from allozyme analysis in that they do not explicitly yield information of allelism and heterozygosity. Therefore, in order to infer these parameters, assumptions must be made concerning the relationship of observed data to the underlying DNA architecture. In particular, assessments of population genetic diversity from DNA fingerprint data have employed at least three approaches based on different assumptions about the data. The authors compare different statistics, using a previously presented set of RAPD fingerprints of three populations of brown bullhead catfish. Furthermore, the behavior of these statistics is examined--as the sample sizes of fish/population and polymorphisms/fish are varied. Sample sizes are reduced either randomly or, in the case of polymorphisms (which are electrophoretic bands), systematically pruned using the criteria of high reproducibility between duplicate samples for inclusion of data. Implications for sampling individuals and loci in assessments of population genetic diversities are discussed. Concern about population N value and statistical power is very relevant to field situations where individuals available for sampling may be limited in number.

  17. Estimation of social value of statistical life using willingness-to-pay method in Nanjing, China.

    PubMed

    Yang, Zhao; Liu, Pan; Xu, Xin

    2016-10-01

    Rational decision making regarding the safety related investment programs greatly depends on the economic valuation of traffic crashes. The primary objective of this study was to estimate the social value of statistical life in the city of Nanjing in China. A stated preference survey was conducted to investigate travelers' willingness to pay for traffic risk reduction. Face-to-face interviews were conducted at stations, shopping centers, schools, and parks in different districts in the urban area of Nanjing. The respondents were categorized into two groups, including motorists and non-motorists. Both the binary logit model and mixed logit model were developed for the two groups of people. The results revealed that the mixed logit model is superior to the fixed coefficient binary logit model. The factors that significantly affect people's willingness to pay for risk reduction include income, education, gender, age, drive age (for motorists), occupation, whether the charged fees were used to improve private vehicle equipment (for motorists), reduction in fatality rate, and change in travel cost. The Monte Carlo simulation method was used to generate the distribution of value of statistical life (VSL). Based on the mixed logit model, the VSL had a mean value of 3,729,493 RMB ($586,610) with a standard deviation of 2,181,592 RMB ($343,142) for motorists; and a mean of 3,281,283 RMB ($505,318) with a standard deviation of 2,376,975 RMB ($366,054) for non-motorists. Using the tax system to illustrate the contribution of different income groups to social funds, the social value of statistical life was estimated. The average social value of statistical life was found to be 7,184,406 RMB ($1,130,032). PMID:27178028

  18. Statistical physics inspired methods to assign statistical significance in bioinformatics and proteomics: From sequence comparison to mass spectrometry based peptide sequencing

    NASA Astrophysics Data System (ADS)

    Alves, Gelio

    After the sequencing of many complete genomes, we are in a post-genomic era in which the most important task has changed from gathering genetic information to organizing the mass of data as well as under standing how components interact with each other. The former is usually undertaking using bioinformatics methods, while the latter task is generally termed proteomics. Success in both parts demands correct statistical significance assignments for results found. In my dissertation. I study two concrete examples: global sequence alignment statistics and peptide sequencing/identification using mass spectrometry. High-performance liquid chromatography coupled to a mass spectrometer (HPLC/MS/MS), enabling peptide identifications and thus protein identifications, has become the tool of choice in large-scale proteomics experiments. Peptide identification is usually done by database searches methods. The lack of robust statistical significance assignment among current methods motivated the development of a novel de novo algorithm, RAId, whose score statistics then provide statistical significance for high scoring peptides found in our custom, enzyme-digested peptide library. The ease of incorporating post-translation modifications is another important feature of RAId. To organize the massive protein/DNA data accumulated, biologists often cluster proteins according to their similarity via tools such as sequence alignment. Homologous proteins share similar domains. To assess the similarity of two domains usually requires alignment from head to toe, ie. a global alignment. A good alignment score statistics with an appropriate null model enable us to distinguish the biologically meaningful similarity from chance similarity. There has been much progress in local alignment statistics, which characterize score statistics when alignments tend to appear as a short segment of the whole sequence. For global alignment, which is useful in domain alignment, there is still much room for

  19. Whole vertebral bone segmentation method with a statistical intensity-shape model based approach

    NASA Astrophysics Data System (ADS)

    Hanaoka, Shouhei; Fritscher, Karl; Schuler, Benedikt; Masutani, Yoshitaka; Hayashi, Naoto; Ohtomo, Kuni; Schubert, Rainer

    2011-03-01

    An automatic segmentation algorithm for the vertebrae in human body CT images is presented. Especially we focused on constructing and utilizing 4 different statistical intensity-shape combined models for the cervical, upper / lower thoracic and lumbar vertebrae, respectively. For this purpose, two previously reported methods were combined: a deformable model-based initial segmentation method and a statistical shape-intensity model-based precise segmentation method. The former is used as a pre-processing to detect the position and orientation of each vertebra, which determines the initial condition for the latter precise segmentation method. The precise segmentation method needs prior knowledge on both the intensities and the shapes of the objects. After PCA analysis of such shape-intensity expressions obtained from training image sets, vertebrae were parametrically modeled as a linear combination of the principal component vectors. The segmentation of each target vertebra was performed as fitting of this parametric model to the target image by maximum a posteriori estimation, combined with the geodesic active contour method. In the experimental result by using 10 cases, the initial segmentation was successful in 6 cases and only partially failed in 4 cases (2 in the cervical area and 2 in the lumbo-sacral). In the precise segmentation, the mean error distances were 2.078, 1.416, 0.777, 0.939 mm for cervical, upper and lower thoracic, lumbar spines, respectively. In conclusion, our automatic segmentation algorithm for the vertebrae in human body CT images showed a fair performance for cervical, thoracic and lumbar vertebrae.

  20. Jacobian integration method increases the statistical power to measure gray matter atrophy in multiple sclerosis☆

    PubMed Central

    Nakamura, Kunio; Guizard, Nicolas; Fonov, Vladimir S.; Narayanan, Sridar; Collins, D. Louis; Arnold, Douglas L.

    2013-01-01

    Gray matter atrophy provides important insights into neurodegeneration in multiple sclerosis (MS) and can be used as a marker of neuroprotection in clinical trials. Jacobian integration is a method for measuring volume change that uses integration of the local Jacobian determinants of the nonlinear deformation field registering two images, and is a promising tool for measuring gray matter atrophy. Our main objective was to compare the statistical power of the Jacobian integration method to commonly used methods in terms of the sample size required to detect a treatment effect on gray matter atrophy. We used multi-center longitudinal data from relapsing–remitting MS patients and evaluated combinations of cross-sectional and longitudinal pre-processing with SIENAX/FSL, SPM, and FreeSurfer, as well as the Jacobian integration method. The Jacobian integration method outperformed these other commonly used methods, reducing the required sample size by a factor of 4–5. The results demonstrate the advantage of using the Jacobian integration method to assess neuroprotection in MS clinical trials. PMID:24266007

  1. A comparison of dynamical and statistical downscaling methods for regional wave climate projections along French coastlines.

    NASA Astrophysics Data System (ADS)

    Laugel, Amélie; Menendez, Melisa; Benoit, Michel; Mattarolo, Giovanni; Mendez, Fernando

    2013-04-01

    Wave climate forecasting is a major issue for numerous marine and coastal related activities, such as offshore industries, flooding risks assessment and wave energy resource evaluation, among others. Generally, there are two main ways to predict the impacts of the climate change on the wave climate at regional scale: the dynamical and the statistical downscaling of GCM (Global Climate Model). In this study, both methods have been applied on the French coast (Atlantic , English Channel and North Sea shoreline) under three climate change scenarios (A1B, A2, B1) simulated with the GCM ARPEGE-CLIMAT, from Météo-France (AR4, IPCC). The aim of the work is to characterise the wave climatology of the 21st century and compare the statistical and dynamical methods pointing out advantages and disadvantages of each approach. The statistical downscaling method proposed by the Environmental Hydraulics Institute of Cantabria (Spain) has been applied (Menendez et al., 2011). At a particular location, the sea-state climate (Predictand Y) is defined as a function, Y=f(X), of several atmospheric circulation patterns (Predictor X). Assuming these climate associations between predictor and predictand are stationary, the statistical approach has been used to project the future wave conditions with reference to the GCM. The statistical relations between predictor and predictand have been established over 31 years, from 1979 to 2009. The predictor is built as the 3-days-averaged squared sea level pressure gradient from the hourly CFSR database (Climate Forecast System Reanalysis, http://cfs.ncep.noaa.gov/cfsr/). The predictand has been extracted from the 31-years hindcast sea-state database ANEMOC-2 performed with the 3G spectral wave model TOMAWAC (Benoit et al., 1996), developed at EDF R&D LNHE and Saint-Venant Laboratory for Hydraulics and forced by the CFSR 10m wind field. Significant wave height, peak period and mean wave direction have been extracted with an hourly-resolution at

  2. Adequate iodine levels in healthy pregnant women. A cross-sectional survey of dietary intake in Turkey

    PubMed Central

    Kasap, Burcu; Akbaba, Gülhan; Yeniçeri, Emine N.; Akın, Melike N.; Akbaba, Eren; Öner, Gökalp; Turhan, Nilgün Ö.; Duru, Mehmet E.

    2016-01-01

    Objectives: To assess current iodine levels and related factors among healthy pregnant women. Methods: In this cross-sectional, hospital-based study, healthy pregnant women (n=135) were scanned for thyroid volume, provided urine samples for urinary iodine concentration and completed a questionnaire including sociodemographic characteristics and dietary habits targeted for iodine consumption at the Department of Obstetrics and Gynecology, School of Medicine, Muğla Sıtkı Koçman University, Muğla, Turkey, between August 2014 and February 2015. Sociodemographic data were analyzed by simple descriptive statistics. Results: Median urinary iodine concentration was 222.0 µg/L, indicating adequate iodine intake during pregnancy. According to World Health Organization (WHO) criteria, 28.1% of subjects had iodine deficiency, 34.1% had adequate iodine intake, 34.8% had more than adequate iodine intake, and 3.0% had excessive iodine intake during pregnancy. Education level, higher monthly income, current employment, consuming iodized salt, and adding salt to food during, or after cooking were associated with higher urinary iodine concentration. Conclusion: Iodine status of healthy pregnant women was adequate, although the percentage of women with more than adequate iodine intake was higher than the reported literature. PMID:27279519

  3. Biomarkers for pancreatic cancer: Recent achievements in proteomics and genomics through classical and multivariate statistical methods

    PubMed Central

    Marengo, Emilio; Robotti, Elisa

    2014-01-01

    Pancreatic cancer (PC) is one of the most aggressive and lethal neoplastic diseases. A valid alternative to the usual invasive diagnostic tools would certainly be the determination of biomarkers in peripheral fluids to provide less invasive tools for early diagnosis. Nowadays, biomarkers are generally investigated mainly in peripheral blood and tissues through high-throughput omics techniques comparing control vs pathological samples. The results can be evaluated by two main strategies: (1) classical methods in which the identification of significant biomarkers is accomplished by monovariate statistical tests where each biomarker is considered as independent from the others; and (2) multivariate methods, taking into consideration the correlations existing among the biomarkers themselves. This last approach is very powerful since it allows the identification of pools of biomarkers with diagnostic and prognostic performances which are superior to single markers in terms of sensitivity, specificity and robustness. Multivariate techniques are usually applied with variable selection procedures to provide a restricted set of biomarkers with the best predictive ability; however, standard selection methods are usually aimed at the identification of the smallest set of variables with the best predictive ability and exhaustivity is usually neglected. The exhaustive search for biomarkers is instead an important alternative to standard variable selection since it can provide information about the etiology of the pathology by producing a comprehensive set of markers. In this review, the most recent applications of the omics techniques (proteomics, genomics and metabolomics) to the identification of exploratory biomarkers for PC will be presented with particular regard to the statistical methods adopted for their identification. The basic theory related to classical and multivariate methods for identification of biomarkers is presented and then, the most recent applications in

  4. Statistical Methods for Proteomic Biomarker Discovery based on Feature Extraction or Functional Modeling Approaches*

    PubMed Central

    Morris, Jeffrey S.

    2012-01-01

    In recent years, developments in molecular biotechnology have led to the increased promise of detecting and validating biomarkers, or molecular markers that relate to various biological or medical outcomes. Proteomics, the direct study of proteins in biological samples, plays an important role in the biomarker discovery process. These technologies produce complex, high dimensional functional and image data that present many analytical challenges that must be addressed properly for effective comparative proteomics studies that can yield potential biomarkers. Specific challenges include experimental design, preprocessing, feature extraction, and statistical analysis accounting for the inherent multiple testing issues. This paper reviews various computational aspects of comparative proteomic studies, and summarizes contributions I along with numerous collaborators have made. First, there is an overview of comparative proteomics technologies, followed by a discussion of important experimental design and preprocessing issues that must be considered before statistical analysis can be done. Next, the two key approaches to analyzing proteomics data, feature extraction and functional modeling, are described. Feature extraction involves detection and quantification of discrete features like peaks or spots that theoretically correspond to different proteins in the sample. After an overview of the feature extraction approach, specific methods for mass spectrometry (Cromwell) and 2D gel electrophoresis (Pinnacle) are described. The functional modeling approach involves modeling the proteomic data in their entirety as functions or images. A general discussion of the approach is followed by the presentation of a specific method that can be applied, wavelet-based functional mixed models, and its extensions. All methods are illustrated by application to two example proteomic data sets, one from mass spectrometry and one from 2D gel electrophoresis. While the specific methods

  5. Statistical Methods for Proteomic Biomarker Discovery based on Feature Extraction or Functional Modeling Approaches.

    PubMed

    Morris, Jeffrey S

    2012-01-01

    In recent years, developments in molecular biotechnology have led to the increased promise of detecting and validating biomarkers, or molecular markers that relate to various biological or medical outcomes. Proteomics, the direct study of proteins in biological samples, plays an important role in the biomarker discovery process. These technologies produce complex, high dimensional functional and image data that present many analytical challenges that must be addressed properly for effective comparative proteomics studies that can yield potential biomarkers. Specific challenges include experimental design, preprocessing, feature extraction, and statistical analysis accounting for the inherent multiple testing issues. This paper reviews various computational aspects of comparative proteomic studies, and summarizes contributions I along with numerous collaborators have made. First, there is an overview of comparative proteomics technologies, followed by a discussion of important experimental design and preprocessing issues that must be considered before statistical analysis can be done. Next, the two key approaches to analyzing proteomics data, feature extraction and functional modeling, are described. Feature extraction involves detection and quantification of discrete features like peaks or spots that theoretically correspond to different proteins in the sample. After an overview of the feature extraction approach, specific methods for mass spectrometry (Cromwell) and 2D gel electrophoresis (Pinnacle) are described. The functional modeling approach involves modeling the proteomic data in their entirety as functions or images. A general discussion of the approach is followed by the presentation of a specific method that can be applied, wavelet-based functional mixed models, and its extensions. All methods are illustrated by application to two example proteomic data sets, one from mass spectrometry and one from 2D gel electrophoresis. While the specific methods

  6. Testing for Additivity at Select Mixture Groups of Interest Based on Statistical Equivalence Testing Methods

    SciTech Connect

    Stork, LeAnna M.; Gennings, Chris; Carchman, Richard; Carter, Jr., Walter H.; Pounds, Joel G.; Mumtaz, Moiz

    2006-12-01

    Several assumptions, defined and undefined, are used in the toxicity assessment of chemical mixtures. In scientific practice mixture components in the low-dose region, particularly subthreshold doses, are often assumed to behave additively (i.e., zero interaction) based on heuristic arguments. This assumption has important implications in the practice of risk assessment, but has not been experimentally tested. We have developed methodology to test for additivity in the sense of Berenbaum (Advances in Cancer Research, 1981), based on the statistical equivalence testing literature where the null hypothesis of interaction is rejected for the alternative hypothesis of additivity when data support the claim. The implication of this approach is that conclusions of additivity are made with a false positive rate controlled by the experimenter. The claim of additivity is based on prespecified additivity margins, which are chosen using expert biological judgment such that small deviations from additivity, which are not considered to be biologically important, are not statistically significant. This approach is in contrast to the usual hypothesis-testing framework that assumes additivity in the null hypothesis and rejects when there is significant evidence of interaction. In this scenario, failure to reject may be due to lack of statistical power making the claim of additivity problematic. The proposed method is illustrated in a mixture of five organophosphorus pesticides that were experimentally evaluated alone and at relevant mixing ratios. Motor activity was assessed in adult male rats following acute exposure. Four low-dose mixture groups were evaluated. Evidence of additivity is found in three of the four low-dose mixture groups.The proposed method tests for additivity of the whole mixture and does not take into account subset interactions (e.g., synergistic, antagonistic) that may have occurred and cancelled each other out.

  7. Bayesian Statistics.

    ERIC Educational Resources Information Center

    Meyer, Donald L.

    Bayesian statistical methodology and its possible uses in the behavioral sciences are discussed in relation to the solution of problems in both the use and teaching of fundamental statistical methods, including confidence intervals, significance tests, and sampling. The Bayesian model explains these statistical methods and offers a consistent…

  8. A Tool Preference Choice Method for RNA Secondary Structure Prediction by SVM with Statistical Tests

    PubMed Central

    Hor, Chiou-Yi; Yang, Chang-Biau; Chang, Chia-Hung; Tseng, Chiou-Ting; Chen, Hung-Hsin

    2013-01-01

    The Prediction of RNA secondary structures has drawn much attention from both biologists and computer scientists. Many useful tools have been developed for this purpose. These tools have their individual strengths and weaknesses. As a result, based on support vector machines (SVM), we propose a tool choice method which integrates three prediction tools: pknotsRG, RNAStructure, and NUPACK. Our method first extracts features from the target RNA sequence, and adopts two information-theoretic feature selection methods for feature ranking. We propose a method to combine feature selection and classifier fusion in an incremental manner. Our test data set contains 720 RNA sequences, where 225 pseudoknotted RNA sequences are obtained from PseudoBase, and 495 nested RNA sequences are obtained from RNA SSTRAND. The method serves as a preprocessing way in analyzing RNA sequences before the RNA secondary structure prediction tools are employed. In addition, the performance of various configurations is subject to statistical tests to examine their significance. The best base-pair accuracy achieved is 75.5%, which is obtained by the proposed incremental method, and is significantly higher than 68.8%, which is associated with the best predictor, pknotsRG. PMID:23641141

  9. A statistical method for assessing network stability using the Chow test.

    PubMed

    Sotirakopoulos, Kostas; Barham, Richard; Piper, Ben; Nencini, Luca

    2015-10-01

    A statistical method is proposed for the assessment of stability in noise monitoring networks. The technique makes use of a variation of the Chow test applied between multiple measurement nodes placed at different locations and its novelty lies in the way it utilises a simple statistical test based on linear regression to uncover complex issues that can be difficult to expose otherwise. Measurements collected by a noise monitoring network deployed in the center of Pisa are used to demonstrate the capabilities and limitations of the test. It is shown that even in urban environments, where great soundscape variations are exhibited, accurate and robust results can be produced regardless of the proximity of the compared sensors as long as they are located in acoustically similar environments. Also it is shown that variations of the same method can be applied for self-testing on data collected by single stations. Finally it is presented that the versatility of the test makes it suitable for detection of various types of issues that can occur in real life network implementations; from slow drifts away from calibration, to severe, abrupt failures and noise floor shifts. PMID:26370835

  10. A Statistical Method for Assessing Peptide Identification Confidence in Accurate Mass and Time Tag Proteomics

    SciTech Connect

    Stanley, Jeffrey R.; Adkins, Joshua N.; Slysz, Gordon W.; Monroe, Matthew E.; Purvine, Samuel O.; Karpievitch, Yuliya V.; Anderson, Gordon A.; Smith, Richard D.; Dabney, Alan R.

    2011-07-15

    High-throughput proteomics is rapidly evolving to require high mass measurement accuracy for a variety of different applications. Increased mass measurement accuracy in bottom-up proteomics specifically allows for an improved ability to distinguish and characterize detected MS features, which may in turn be identified by, e.g., matching to entries in a database for both precursor and fragmentation mass identification methods. Many tools exist with which to score the identification of peptides from LC-MS/MS measurements or to assess matches to an accurate mass and time (AMT) tag database, but these two calculations remain distinctly unrelated. Here we present a statistical method, Statistical Tools for AMT tag Confidence (STAC), which extends our previous work incorporating prior probabilities of correct sequence identification from LC-MS/MS, as well as the quality with which LC-MS features match AMT tags, to evaluate peptide identification confidence. Compared to existing tools, we are able to obtain significantly more high-confidence peptide identifications at a given false discovery rate and additionally assign confidence estimates to individual peptide identifications. Freely available software implementations of STAC are available in both command line and as a Windows graphical application.

  11. Higher-order statistical moments and a procedure that detects potentially anomalous years as two alternative methods describing alterations in continuous environmental data

    USGS Publications Warehouse

    Arismendi, Ivan; Johnson, Sherri L.; Dunham, Jason

    2015-01-01

    Statistics of central tendency and dispersion may not capture relevant or desired characteristics of the distribution of continuous phenomena and, thus, they may not adequately describe temporal patterns of change. Here, we present two methodological approaches that can help to identify temporal changes in environmental regimes. First, we use higher-order statistical moments (skewness and kurtosis) to examine potential changes of empirical distributions at decadal extents. Second, we adapt a statistical procedure combining a non-metric multidimensional scaling technique and higher density region plots to detect potentially anomalous years. We illustrate the use of these approaches by examining long-term stream temperature data from minimally and highly human-influenced streams. In particular, we contrast predictions about thermal regime responses to changing climates and human-related water uses. Using these methods, we effectively diagnose years with unusual thermal variability and patterns in variability through time, as well as spatial variability linked to regional and local factors that influence stream temperature. Our findings highlight the complexity of responses of thermal regimes of streams and reveal their differential vulnerability to climate warming and human-related water uses. The two approaches presented here can be applied with a variety of other continuous phenomena to address historical changes, extreme events, and their associated ecological responses.

  12. Technical Note: Higher-order statistical moments and a procedure that detects potentially anomalous years as two alternative methods describing alterations in continuous environmental data

    NASA Astrophysics Data System (ADS)

    Arismendi, I.; Johnson, S. L.; Dunham, J. B.

    2015-03-01

    Statistics of central tendency and dispersion may not capture relevant or desired characteristics of the distribution of continuous phenomena and, thus, they may not adequately describe temporal patterns of change. Here, we present two methodological approaches that can help to identify temporal changes in environmental regimes. First, we use higher-order statistical moments (skewness and kurtosis) to examine potential changes of empirical distributions at decadal extents. Second, we adapt a statistical procedure combining a non-metric multidimensional scaling technique and higher density region plots to detect potentially anomalous years. We illustrate the use of these approaches by examining long-term stream temperature data from minimally and highly human-influenced streams. In particular, we contrast predictions about thermal regime responses to changing climates and human-related water uses. Using these methods, we effectively diagnose years with unusual thermal variability and patterns in variability through time, as well as spatial variability linked to regional and local factors that influence stream temperature. Our findings highlight the complexity of responses of thermal regimes of streams and reveal their differential vulnerability to climate warming and human-related water uses. The two approaches presented here can be applied with a variety of other continuous phenomena to address historical changes, extreme events, and their associated ecological responses.

  13. Segmentation of Brain MRI Using SOM-FCM-Based Method and 3D Statistical Descriptors

    PubMed Central

    Ortiz, Andrés; Palacio, Antonio A.; Górriz, Juan M.; Ramírez, Javier; Salas-González, Diego

    2013-01-01

    Current medical imaging systems provide excellent spatial resolution, high tissue contrast, and up to 65535 intensity levels. Thus, image processing techniques which aim to exploit the information contained in the images are necessary for using these images in computer-aided diagnosis (CAD) systems. Image segmentation may be defined as the process of parcelling the image to delimit different neuroanatomical tissues present on the brain. In this paper we propose a segmentation technique using 3D statistical features extracted from the volume image. In addition, the presented method is based on unsupervised vector quantization and fuzzy clustering techniques and does not use any a priori information. The resulting fuzzy segmentation method addresses the problem of partial volume effect (PVE) and has been assessed using real brain images from the Internet Brain Image Repository (IBSR). PMID:23762192

  14. Affinity measurement of single chain antibodies: a mathematical method facilitated by statistical software SigmaPlot.

    PubMed

    Safdari, Yaghoub; Farajnia, Safar; Asgharzadeh, Mohammad; Khalili, Masoumeh; Jaliani, Hossein Zarei

    2014-02-01

    Because they are monovalent for antigen, single chain antibodies display a different antibody-antigen interaction pattern from that of full-length antibodies. Using the law of mass action and considering the antibody-antigen binding pattern at OD-100% and OD-50% points, we introduced a formula for estimating single chain antibody affinity. Sigmoid curves of optical density values versus antibody concentrations were drawn and used to determine antibody concentrations at OD-50% points using statistical software SigmaPlot. The OD-50% points were then used to calculate the affinity via the mathematical formula. A software-adapted format of the equation is also presented for further facilitation of the calculation process. The accuracy of this method for affinity calculation was proved by surface plasma resonance. This method offers a precise evaluation of antibody affinity without requiring special material or apparatus, making it possible to be performed in any biological laboratory with minimum facilities. PMID:24555931

  15. SAXS Merge: an automated statistical method to merge SAXS profiles using Gaussian processes.

    PubMed

    Spill, Yannick G; Kim, Seung Joong; Schneidman-Duhovny, Dina; Russel, Daniel; Webb, Ben; Sali, Andrej; Nilges, Michael

    2014-01-01

    Small-angle X-ray scattering (SAXS) is an experimental technique that allows structural information on biomolecules in solution to be gathered. High-quality SAXS profiles have typically been obtained by manual merging of scattering profiles from different concentrations and exposure times. This procedure is very subjective and results vary from user to user. Up to now, no robust automatic procedure has been published to perform this step, preventing the application of SAXS to high-throughput projects. Here, SAXS Merge, a fully automated statistical method for merging SAXS profiles using Gaussian processes, is presented. This method requires only the buffer-subtracted SAXS profiles in a specific order. At the heart of its formulation is non-linear interpolation using Gaussian processes, which provides a statement of the problem that accounts for correlation in the data. PMID:24365937

  16. Statistical methods for astronomical data with upper limits. I - Univariate distributions

    NASA Technical Reports Server (NTRS)

    Feigelson, E. D.; Nelson, P. I.

    1985-01-01

    The statistical treatment of univariate censored data is discussed. A heuristic derivation of the Kaplan-Meier maximum-likelihood estimator from first principles is presented which results in an expression amenable to analytic error analysis. Methods for comparing two or more censored samples are given along with simple computational examples, stressing the fact that most astronomical problems involve upper limits while the standard mathematical methods require lower limits. The application of univariate survival analysis to six data sets in the recent astrophysical literature is described, and various aspects of the use of survival analysis in astronomy, such as the limitations of various two-sample tests and the role of parametric modelling, are discussed.

  17. Effect of the Target Motion Sampling Temperature Treatment Method on the Statistics and Performance

    NASA Astrophysics Data System (ADS)

    Viitanen, Tuomas; Leppänen, Jaakko

    2014-06-01

    Target Motion Sampling (TMS) is a stochastic on-the-fly temperature treatment technique that is being developed as a part of the Monte Carlo reactor physics code Serpent. The method provides for modeling of arbitrary temperatures in continuous-energy Monte Carlo tracking routines with only one set of cross sections stored in the computer memory. Previously, only the performance of the TMS method in terms of CPU time per transported neutron has been discussed. Since the effective cross sections are not calculated at any point of a transport simulation with TMS, reaction rate estimators must be scored using sampled cross sections, which is expected to increase the variances and, consequently, to decrease the figures-of-merit. This paper examines the effects of the TMS on the statistics and performance in practical calculations involving reaction rate estimation with collision estimators. Against all expectations it turned out that the usage of sampled response values has no practical effect on the performance of reaction rate estimators when using TMS with elevated basis cross section temperatures (EBT), i.e. the usual way. With 0 Kelvin cross sections a significant increase in the variances of capture rate estimators was observed right below the energy region of unresolved resonances, but at these energies the figures-of-merit could be increased using a simple resampling technique to decrease the variances of the responses. It was, however, noticed that the usage of the TMS method increases the statistical deviances of all estimators, including the flux estimator, by tens of percents in the vicinity of very strong resonances. This effect is actually not related to the usage of sampled responses, but is instead an inherent property of the TMS tracking method and concerns both EBT and 0 K calculations.

  18. PAFit: A Statistical Method for Measuring Preferential Attachment in Temporal Complex Networks

    PubMed Central

    Pham, Thong; Sheridan, Paul; Shimodaira, Hidetoshi

    2015-01-01

    Preferential attachment is a stochastic process that has been proposed to explain certain topological features characteristic of complex networks from diverse domains. The systematic investigation of preferential attachment is an important area of research in network science, not only for the theoretical matter of verifying whether this hypothesized process is operative in real-world networks, but also for the practical insights that follow from knowledge of its functional form. Here we describe a maximum likelihood based estimation method for the measurement of preferential attachment in temporal complex networks. We call the method PAFit, and implement it in an R package of the same name. PAFit constitutes an advance over previous methods primarily because we based it on a nonparametric statistical framework that enables attachment kernel estimation free of any assumptions about its functional form. We show this results in PAFit outperforming the popular methods of Jeong and Newman in Monte Carlo simulations. What is more, we found that the application of PAFit to a publically available Flickr social network dataset yielded clear evidence for a deviation of the attachment kernel from the popularly assumed log-linear form. Independent of our main work, we provide a correction to a consequential error in Newman’s original method which had evidently gone unnoticed since its publication over a decade ago. PMID:26378457

  19. Statistical methods for temporal and space–time analysis of community composition data†

    PubMed Central

    Legendre, Pierre; Gauthier, Olivier

    2014-01-01

    This review focuses on the analysis of temporal beta diversity, which is the variation in community composition along time in a study area. Temporal beta diversity is measured by the variance of the multivariate community composition time series and that variance can be partitioned using appropriate statistical methods. Some of these methods are classical, such as simple or canonical ordination, whereas others are recent, including the methods of temporal eigenfunction analysis developed for multiscale exploration (i.e. addressing several scales of variation) of univariate or multivariate response data, reviewed, to our knowledge for the first time in this review. These methods are illustrated with ecological data from 13 years of benthic surveys in Chesapeake Bay, USA. The following methods are applied to the Chesapeake data: distance-based Moran's eigenvector maps, asymmetric eigenvector maps, scalogram, variation partitioning, multivariate correlogram, multivariate regression tree, and two-way MANOVA to study temporal and space–time variability. Local (temporal) contributions to beta diversity (LCBD indices) are computed and analysed graphically and by regression against environmental variables, and the role of species in determining the LCBD values is analysed by correlation analysis. A tutorial detailing the analyses in the R language is provided in an appendix. PMID:24430848

  20. A statistical gap-filling method to interpolate global monthly surface ocean carbon dioxide data

    NASA Astrophysics Data System (ADS)

    Jones, Steve D.; Le Quéré, Corinne; Rödenbeck, Christian; Manning, Andrew C.; Olsen, Are

    2015-12-01

    We have developed a statistical gap-filling method adapted to the specific coverage and properties of observed fugacity of surface ocean CO2 (fCO2). We have used this method to interpolate the Surface Ocean CO2 Atlas (SOCAT) v2 database on a 2.5°×2.5° global grid (south of 70°N) for 1985-2011 at monthly resolution. The method combines a spatial interpolation based on a "radius of influence" to determine nearby similar fCO2 values with temporal harmonic and cubic spline curve-fitting, and also fits long-term trends and seasonal cycles. Interannual variability is established using deviations of observations from the fitted trends and seasonal cycles. An uncertainty is computed for all interpolated values based on the spatial and temporal range of the interpolation. Tests of the method using model data show that it performs as well as or better than previous regional interpolation methods, but in addition it provides a near-global and interannual coverage.

  1. Computer program for the calculation of grain size statistics by the method of moments

    USGS Publications Warehouse

    Sawyer, Michael B.

    1977-01-01

    A computer program is presented for a Hewlett-Packard Model 9830A desk-top calculator (1) which calculates statistics using weight or point count data from a grain-size analysis. The program uses the method of moments in contrast to the more commonly used but less inclusive graphic method of Folk and Ward (1957). The merits of the program are: (1) it is rapid; (2) it can accept data in either grouped or ungrouped format; (3) it allows direct comparison with grain-size data in the literature that have been calculated by the method of moments; (4) it utilizes all of the original data rather than percentiles from the cumulative curve as in the approximation technique used by the graphic method; (5) it is written in the computer language BASIC, which is easily modified and adapted to a wide variety of computers; and (6) when used in the HP-9830A, it does not require punching of data cards. The method of moments should be used only if the entire sample has been measured and the worker defines the measured grain-size range. (1) Use of brand names in this paper does not imply endorsement of these products by the U.S. Geological Survey.

  2. [Concentration retrieving method of SO2 using differential optical absorption spectroscopy based on statistics].

    PubMed

    Liu, Bin; Sun, Chang-Ku; Zhang, Chi; Zhao, Yu-Mei; Liu, Jun-Ping

    2011-01-01

    A concentration retrieving method using statistics is presented, which is applied in differential optical absorption spectroscopy (DOAS) for measuring the concentration of SO2. The method uses the standard deviation of the differential absorption to represents the gas concentration. Principle component analysis (PCA) method is used to process the differential absorption spectrum. In the method, the basis data for the concentration retrieval of SO2 is the combination of the PCA processing result, the correlation coefficient, and the standard deviation of the differential absorption. The method is applied to a continuous emission monitoring system (CEMS) with optical path length of 0.3 m. Its measuring range for SO2 concentration is 0-5 800 mg x m(-3). The nonlinear calibration and the temperature compensation for the system were executed. The full scale error of the retrieving concentration is less than 0.7% FS. And the measuring result is -4.54 mg x m(-3) when the concentration of SO2 is zero. PMID:21428087

  3. Statistical Classification of Soft Solder Alloys by Laser-Induced Breakdown Spectroscopy: Review of Methods

    NASA Astrophysics Data System (ADS)

    Zdunek, R.; Nowak, M.; Pliński, E.

    2016-02-01

    This paper reviews machine-learning methods that are nowadays the most frequently used for the supervised classification of spectral signals in laser-induced breakdown spectroscopy (LIBS). We analyze and compare various statistical classification methods, such as linear discriminant analysis (LDA), quadratic discriminant analysis (QDA), partial least-squares discriminant analysis (PLS-DA), soft independent modeling of class analogy (SIMCA), support vector machine (SVM), naive Bayes method, probabilistic neural networks (PNN), and K-nearest neighbor (KNN) method. The theoretical considerations are supported with experiments conducted for real soft-solder-alloy spectra obtained using LIBS. We consider two decision problems: binary and multiclass classification. The former is used to distinguish overheated soft solders from their normal versions. The latter aims to assign a testing sample to a given group of materials. The measurements are obtained for several laser-energy values, projection masks, and numbers of laser shots. Using cross-validation, we evaluate the above classification methods in terms of their usefulness in solving both classification problems.

  4. Statistical methods for the analysis of a screening test for chronic beryllium disease

    SciTech Connect

    Frome, E.L.; Neubert, R.L.; Smith, M.H.; Littlefield, L.G.; Colyer, S.P.

    1994-10-01

    The lymphocyte proliferation test (LPT) is a noninvasive screening procedure used to identify persons who may have chronic beryllium disease. A practical problem in the analysis of LPT well counts is the occurrence of outlying data values (approximately 7% of the time). A log-linear regression model is used to describe the expected well counts for each set of test conditions. The variance of the well counts is proportional to the square of the expected counts, and two resistant regression methods are used to estimate the parameters of interest. The first approach uses least absolute values (LAV) on the log of the well counts to estimate beryllium stimulation indices (SIs) and the coefficient of variation. The second approach uses a resistant regression version of maximum quasi-likelihood estimation. A major advantage of the resistant regression methods is that it is not necessary to identify and delete outliers. These two new methods for the statistical analysis of the LPT data and the outlier rejection method that is currently being used are applied to 173 LPT assays. The authors strongly recommend the LAV method for routine analysis of the LPT.

  5. Application of a statistical downscaling method to detect inhomogeneities in a temperature time series

    NASA Astrophysics Data System (ADS)

    Marcos, R.; Turco, M.; Llasat, M. C.; Quintana-Seguí, P.

    2012-04-01

    In the context of climate studies, the analysis of long homogeneous time series is of the utmost importance. A homogeneous climate series is defined as a series whose variations are caused only by changes in weather and climate (Conrad and Pollak, 1950). Unfortunately, a time series is often affected by one or more artificial inhomogeneities. Regardless of the type and the effect of inhomogeneities, the analysis of a non-homogeneous series can be misleading. Consequently, it is crucial to determine, assign and adjust any discontinuities in the data, especially in those reference series used in climate change studies. The Twentieth Century Reanalysis (20CR) data can provide an independent estimate of, among other variables, surface temperature. However, the difference in scale affects its potential use as a tool to detect non-climatic inhomogeneities in a local temperature time series. To avoid this limitation, we propose a new approach based on a parsimonious statistical downscaling method to bridge the gap between reanalysis data and the local temperature time series. This method was applied to two high-quality international reference stations in the North-East of Spain (present in the ECA database, http://eca.knmi.nl/) whose temperature series are used, for example, in the report of climatic change in Catalonia, Cunillera et al., 2009: Ebre (Tortosa) and Fabra (Barcelona), for the periods 1940-2008 and 1914-2008, respectively. Both series show an anomalous period which is clearly identifiable by visual inspection. The statistical downscaling model was calibrated for these stations and independently tested over the reliable periods with good results. The model was then applied to reproduce the doubtful years. The results of the study are in agreement with the metadata: for the Fabra series, the method proposed clearly identifies the artificial inhomogeneity; whilst for the Ebre Observatory, there is no documented change in the station and the suspicious period

  6. A Network-Based Method to Assess the Statistical Significance of Mild Co-Regulation Effects

    PubMed Central

    Horvát, Emőke-Ágnes; Zhang, Jitao David; Uhlmann, Stefan; Sahin, Özgür; Zweig, Katharina Anna

    2013-01-01

    Recent development of high-throughput, multiplexing technology has initiated projects that systematically investigate interactions between two types of components in biological networks, for instance transcription factors and promoter sequences, or microRNAs (miRNAs) and mRNAs. In terms of network biology, such screening approaches primarily attempt to elucidate relations between biological components of two distinct types, which can be represented as edges between nodes in a bipartite graph. However, it is often desirable not only to determine regulatory relationships between nodes of different types, but also to understand the connection patterns of nodes of the same type. Especially interesting is the co-occurrence of two nodes of the same type, i.e., the number of their common neighbours, which current high-throughput screening analysis fails to address. The co-occurrence gives the number of circumstances under which both of the biological components are influenced in the same way. Here we present SICORE, a novel network-based method to detect pairs of nodes with a statistically significant co-occurrence. We first show the stability of the proposed method on artificial data sets: when randomly adding and deleting observations we obtain reliable results even with noise exceeding the expected level in large-scale experiments. Subsequently, we illustrate the viability of the method based on the analysis of a proteomic screening data set to reveal regulatory patterns of human microRNAs targeting proteins in the EGFR-driven cell cycle signalling system. Since statistically significant co-occurrence may indicate functional synergy and the mechanisms underlying canalization, and thus hold promise in drug target identification and therapeutic development, we provide a platform-independent implementation of SICORE with a graphical user interface as a novel tool in the arsenal of high-throughput screening analysis. PMID:24039936

  7. Understanding the Negative Graduate Student Perceptions of Required Statistics and Research Methods Courses: Implications for Programs and Faculty

    ERIC Educational Resources Information Center

    Coleman, Charles; Conrad, Cynthia

    2007-01-01

    The authors of this study endeavor to explore the negative opinions and perceptions of graduate students in business and social science programs, regarding their required statistics and research methods courses. The general sense of instructors of such courses is that students dread and resent having to take courses dealing with statistics and…

  8. Internet Approach versus Lecture and Lab-Based Approach for Teaching an Introductory Statistical Methods Course: Students' Opinions

    ERIC Educational Resources Information Center

    Johnson, H. Dean; Dasgupta, Nairanjana; Zhang, Hao; Evans, Marc A.

    2009-01-01

    The use of the Internet as a teaching tool continues to grow in popularity at colleges and universities. We consider, from the students' perspective, the use of an Internet approach compared to a lecture and lab-based approach for teaching an introductory course in statistical methods. We conducted a survey of introductory statistics students.…

  9. Exploring the use of statistical process control methods to assess course changes

    NASA Astrophysics Data System (ADS)

    Vollstedt, Ann-Marie

    This dissertation pertains to the field of Engineering Education. The Department of Mechanical Engineering at the University of Nevada, Reno (UNR) is hosting this dissertation under a special agreement. This study was motivated by the desire to find an improved, quantitative measure of student quality that is both convenient to use and easy to evaluate. While traditional statistical analysis tools such as ANOVA (analysis of variance) are useful, they are somewhat time consuming and are subject to error because they are based on grades, which are influenced by numerous variables, independent of student ability and effort (e.g. inflation and curving). Additionally, grades are currently the only measure of quality in most engineering courses even though most faculty agree that grades do not accurately reflect student quality. Based on a literature search, in this study, quality was defined as content knowledge, cognitive level, self efficacy, and critical thinking. Nineteen treatments were applied to a pair of freshmen classes in an effort in increase the qualities. The qualities were measured via quiz grades, essays, surveys, and online critical thinking tests. Results from the quality tests were adjusted and filtered prior to analysis. All test results were subjected to Chauvenet's criterion in order to detect and remove outlying data. In addition to removing outliers from data sets, it was felt that individual course grades needed adjustment to accommodate for the large portion of the grade that was defined by group work. A new method was developed to adjust grades within each group based on the residual of the individual grades within the group and the portion of the course grade defined by group work. It was found that the grade adjustment method agreed 78% of the time with the manual ii grade changes instructors made in 2009, and also increased the correlation between group grades and individual grades. Using these adjusted grades, Statistical Process Control

  10. Is a vegetarian diet adequate for children.

    PubMed

    Hackett, A; Nathan, I; Burgess, L

    1998-01-01

    The number of people who avoid eating meat is growing, especially among young people. Benefits to health from a vegetarian diet have been reported in adults but it is not clear to what extent these benefits are due to diet or to other aspects of lifestyles. In children concern has been expressed concerning the adequacy of vegetarian diets especially with regard to growth. The risks/benefits seem to be related to the degree of restriction of he diet; anaemia is probably both the main and the most serious risk but this also applies to omnivores. Vegan diets are more likely to be associated with malnutrition, especially if the diets are the result of authoritarian dogma. Overall, lacto-ovo-vegetarian children consume diets closer to recommendations than omnivores and their pre-pubertal growth is at least as good. The simplest strategy when becoming vegetarian may involve reliance on vegetarian convenience foods which are not necessarily superior in nutritional composition. The vegetarian sector of the food industry could do more to produce foods closer to recommendations. Vegetarian diets can be, but are not necessarily, adequate for children, providing vigilance is maintained, particularly to ensure variety. Identical comments apply to omnivorous diets. Three threats to the diet of children are too much reliance on convenience foods, lack of variety and lack of exercise. PMID:9670174

  11. [The principal components analysis--method to classify the statistical variables with applications in medicine].

    PubMed

    Dascălu, Cristina Gena; Antohe, Magda Ecaterina

    2009-01-01

    Based on the eigenvalues and the eigenvectors analysis, the principal component analysis has the purpose to identify the subspace of the main components from a set of parameters, which are enough to characterize the whole set of parameters. Interpreting the data for analysis as a cloud of points, we find through geometrical transformations the directions where the cloud's dispersion is maximal--the lines that pass through the cloud's center of weight and have a maximal density of points around them (by defining an appropriate criteria function and its minimization. This method can be successfully used in order to simplify the statistical analysis on questionnaires--because it helps us to select from a set of items only the most relevant ones, which cover the variations of the whole set of data. For instance, in the presented sample we started from a questionnaire with 28 items and, applying the principal component analysis we identified 7 principal components--or main items--fact that simplifies significantly the further data statistical analysis. PMID:21495371

  12. Quantitative Imaging Biomarkers: A Review of Statistical Methods for Computer Algorithm Comparisons

    PubMed Central

    2014-01-01

    Quantitative biomarkers from medical images are becoming important tools for clinical diagnosis, staging, monitoring, treatment planning, and development of new therapies. While there is a rich history of the development of quantitative imaging biomarker (QIB) techniques, little attention has been paid to the validation and comparison of the computer algorithms that implement the QIB measurements. In this paper we provide a framework for QIB algorithm comparisons. We first review and compare various study designs, including designs with the true value (e.g. phantoms, digital reference images, and zero-change studies), designs with a reference standard (e.g. studies testing equivalence with a reference standard), and designs without a reference standard (e.g. agreement studies and studies of algorithm precision). The statistical methods for comparing QIB algorithms are then presented for various study types using both aggregate and disaggregate approaches. We propose a series of steps for establishing the performance of a QIB algorithm, identify limitations in the current statistical literature, and suggest future directions for research. PMID:24919829

  13. Interactive statistical-distribution-analysis program utilizing numerical and graphical methods

    SciTech Connect

    Glandon, S. R.; Fields, D. E.

    1982-04-01

    The TERPED/P program is designed to facilitate the quantitative analysis of experimental data, determine the distribution function that best describes the data, and provide graphical representations of the data. This code differs from its predecessors, TEDPED and TERPED, in that a printer-plotter has been added for graphical output flexibility. The addition of the printer-plotter provides TERPED/P with a method of generating graphs that is not dependent on DISSPLA, Integrated Software Systems Corporation's confidential proprietary graphics package. This makes it possible to use TERPED/P on systems not equipped with DISSPLA. In addition, the printer plot is usually produced more rapidly than a high-resolution plot can be generated. Graphical and numerical tests are performed on the data in accordance with the user's assumption of normality or lognormality. Statistical analysis options include computation of the chi-squared statistic and its significance level and the Kolmogorov-Smirnov one-sample test confidence level for data sets of more than 80 points. Plots can be produced on a Calcomp paper plotter, a FR80 film plotter, or a graphics terminal using the high-resolution, DISSPLA-dependent plotter or on a character-type output device by the printer-plotter. The plots are of cumulative probability (abscissa) versus user-defined units (ordinate). The program was developed on a Digital Equipment Corporation (DEC) PDP-10 and consists of 1500 statements. The language used is FORTRAN-10, DEC's extended version of FORTRAN-IV.

  14. A comparison of different statistical methods analyzing hypoglycemia data using bootstrap simulations.

    PubMed

    Jiang, Honghua; Ni, Xiao; Huster, William; Heilmann, Cory

    2015-01-01

    Hypoglycemia has long been recognized as a major barrier to achieving normoglycemia with intensive diabetic therapies. It is a common safety concern for the diabetes patients. Therefore, it is important to apply appropriate statistical methods when analyzing hypoglycemia data. Here, we carried out bootstrap simulations to investigate the performance of the four commonly used statistical models (Poisson, negative binomial, analysis of covariance [ANCOVA], and rank ANCOVA) based on the data from a diabetes clinical trial. Zero-inflated Poisson (ZIP) model and zero-inflated negative binomial (ZINB) model were also evaluated. Simulation results showed that Poisson model inflated type I error, while negative binomial model was overly conservative. However, after adjusting for dispersion, both Poisson and negative binomial models yielded slightly inflated type I errors, which were close to the nominal level and reasonable power. Reasonable control of type I error was associated with ANCOVA model. Rank ANCOVA model was associated with the greatest power and with reasonable control of type I error. Inflated type I error was observed with ZIP and ZINB models. PMID:24905704

  15. New Developments in the Embedded Statistical Coupling Method: Atomistic/Continuum Crack Propagation

    NASA Technical Reports Server (NTRS)

    Saether, E.; Yamakov, V.; Glaessgen, E.

    2008-01-01

    A concurrent multiscale modeling methodology that embeds a molecular dynamics (MD) region within a finite element (FEM) domain has been enhanced. The concurrent MD-FEM coupling methodology uses statistical averaging of the deformation of the atomistic MD domain to provide interface displacement boundary conditions to the surrounding continuum FEM region, which, in turn, generates interface reaction forces that are applied as piecewise constant traction boundary conditions to the MD domain. The enhancement is based on the addition of molecular dynamics-based cohesive zone model (CZM) elements near the MD-FEM interface. The CZM elements are a continuum interpretation of the traction-displacement relationships taken from MD simulations using Cohesive Zone Volume Elements (CZVE). The addition of CZM elements to the concurrent MD-FEM analysis provides a consistent set of atomistically-based cohesive properties within the finite element region near the growing crack. Another set of CZVEs are then used to extract revised CZM relationships from the enhanced embedded statistical coupling method (ESCM) simulation of an edge crack under uniaxial loading.

  16. Improved Test Planning and Analysis Through the Use of Advanced Statistical Methods

    NASA Technical Reports Server (NTRS)

    Green, Lawrence L.; Maxwell, Katherine A.; Glass, David E.; Vaughn, Wallace L.; Barger, Weston; Cook, Mylan

    2016-01-01

    The goal of this work is, through computational simulations, to provide statistically-based evidence to convince the testing community that a distributed testing approach is superior to a clustered testing approach for most situations. For clustered testing, numerous, repeated test points are acquired at a limited number of test conditions. For distributed testing, only one or a few test points are requested at many different conditions. The statistical techniques of Analysis of Variance (ANOVA), Design of Experiments (DOE) and Response Surface Methods (RSM) are applied to enable distributed test planning, data analysis and test augmentation. The D-Optimal class of DOE is used to plan an optimally efficient single- and multi-factor test. The resulting simulated test data are analyzed via ANOVA and a parametric model is constructed using RSM. Finally, ANOVA can be used to plan a second round of testing to augment the existing data set with new data points. The use of these techniques is demonstrated through several illustrative examples. To date, many thousands of comparisons have been performed and the results strongly support the conclusion that the distributed testing approach outperforms the clustered testing approach.

  17. Krylov iterative methods and synthetic acceleration for transport in binary statistical media

    SciTech Connect

    Fichtl, Erin D; Warsa, James S; Prinja, Anil K

    2008-01-01

    In particle transport applications there are numerous physical constructs in which heterogeneities are randomly distributed. The quantity of interest in these problems is the ensemble average of the flux, or the average of the flux over all possible material 'realizations.' The Levermore-Pomraning closure assumes Markovian mixing statistics and allows a closed, coupled system of equations to be written for the ensemble averages of the flux in each material. Generally, binary statistical mixtures are considered in which there are two (homogeneous) materials and corresponding coupled equations. The solution process is iterative, but convergence may be slow as either or both materials approach the diffusion and/or atomic mix limits. A three-part acceleration scheme is devised to expedite convergence, particularly in the atomic mix-diffusion limit where computation is extremely slow. The iteration is first divided into a series of 'inner' material and source iterations to attenuate the diffusion and atomic mix error modes separately. Secondly, atomic mix synthetic acceleration is applied to the inner material iteration and S{sup 2} synthetic acceleration to the inner source iterations to offset the cost of doing several inner iterations per outer iteration. Finally, a Krylov iterative solver is wrapped around each iteration, inner and outer, to further expedite convergence. A spectral analysis is conducted and iteration counts and computing cost for the new two-step scheme are compared against those for a simple one-step iteration, to which a Krylov iterative method can also be applied.

  18. A new method to obtain uniform distribution of ground control points based on regional statistical information

    NASA Astrophysics Data System (ADS)

    Ma, Chao; An, Wei; Deng, Xinpu

    2015-10-01

    The Ground Control Points (GCPs) is an important source of fundamental data in geometric correction for remote sensing imagery. The quantity, accuracy and distribution of GCPs are three factors which may affect the accuracy of geometric correction. It is generally required that the distribution of GCP should be uniform, so they can fully control the accuracy of mapping regions. In this paper, we establish an objective standard of evaluating the uniformity of the GCPs' distribution based on regional statistical information (RSI), and get an optimal distribution of GCPs. This sampling method is called RSIS for short in this work. The Amounts of GCPs in different regions by equally partitioning the image in regions in different manners are counted which forms a vector called RSI vector in this work. The uniformity of GCPs' distribution can be evaluated by a mathematical quantity of the RSI vector. An optimal distribution of GCPs is obtained by searching the RSI vector with the minimum mathematical quantity. In this paper, the simulation annealing is employed to search the optimal distribution of GCPs that have the minimum mathematical quantity of the RSI vector. Experiments are carried out to test the method proposed in this paper, and sampling designs compared are simple random sampling and universal kriging model-based sampling. The experiments indicate that this method is highly recommended as new GCPs sampling design method for geometric correction of remotely sensed imagery.

  19. A statistical method for treating molecular line opacities. [in cool stellar atmospheres

    NASA Technical Reports Server (NTRS)

    Sneden, C.; Johnson, H. R.; Krupp, B. M.

    1976-01-01

    A method for treating atomic and molecular line opacities in cool stellar atmospheres by a statistical opacity sampling is investigated. Under the usual assumptions of plane-parallel geometry, radiative equilibrium, hydrostatic equilibrium, and LTE, each radiative quantity is computed monochromatically at each chosen frequency and depth without any averaging of the opacity. The number of frequencies needed to allow an accurate integration of the energy flux over a given spectral interval is investigated as a function of depth, including opacity for both CN and C2. This method is extended to the calculation of a model atmosphere of a star, and the effect of the number and placement of frequency points is studied. The method is applied to treating molecular lines of CO, C2, and CN in a cool carbon star. Significant advantages of the opacity sampling method are its flexibility, which permits computation of models having arbitrary variations of chemical composition and of opacity with wavelength and depth, and generalizability to include departures from LTE.

  20. Comparison of three statistical downscaling methods for precipitation in the Hérault and Ebro catchments

    NASA Astrophysics Data System (ADS)

    Lassonde, Sylvain; Vrac, Mathieu; Ruelland, Denis; Dezetter, Alain

    2014-05-01

    The aim of the GICC project "REMedHE" (http://www.remedhe.org) is to evaluate and compare the evolution of water supply capacity under climatic and anthropogenic changes by 2050 on two Mediterranean catchments: the Hérault (South of France) and the Ebro (North East of Spain) catchments. Indeed, the Mediterranean region has been identified as a "hot spot" of climate change, especially for precipitation which is expected to globally decrease while water needs should continue to increase. To perform such a study, it is then necessary to simulate future water flows with hydrological models fed by high-resolution precipitation data representative of the future climate. To generate high-resolution climate simulations, three different statistical downscaling approaches have been applied. The first one consists in a deterministic transfer function based on a Generalized Additive Model (GAM). The second method involves a Stochastic Weather Generator (SWG), simulating local values from probability density functions conditioned by large-scale predictors. The third approach belongs to the "Model Output Statistics" (MOS) family, in bias correcting the large-scale distributions with respect to the local-scale ones, through the Cumulative Distribution Function transform CDFt approach. These statistical downscaling models were calibrated and cross-validated using the SAFRAN dataset (for Hérault catchment), a dataset compiled by HydroSciences Montpellier (for Ebro catchment) as local-scale reference and the National Centers for Environmental Prediction/National Center for Atmospheric Research (NCEP/NCAR) reanalysis outputs as predictors, over two time periods 1959-1984 and 1985-2010. Cross-validation analysis shows that the inter-annual variability of the yearly sum of precipitation from GAM is close to that from SAFRAN. However, daily variability and occurrence frequency are badly represented by GAM. On the opposite, SWG and one version of CDFt allow both the inter-annual and

  1. Application of Statistical Methods of Rain Rate Estimation to Data From The TRMM Precipitation Radar

    NASA Technical Reports Server (NTRS)

    Meneghini, R.; Jones, J. A.; Iguchi, T.; Okamoto, K.; Liao, L.; Busalacchi, Antonio J. (Technical Monitor)

    2000-01-01

    The TRMM Precipitation Radar is well suited to statistical methods in that the measurements over any given region are sparsely sampled in time. Moreover, the instantaneous rain rate estimates are often of limited accuracy at high rain rates because of attenuation effects and at light rain rates because of receiver sensitivity. For the estimation of the time-averaged rain characteristics over an area both errors are relevant. By enlarging the space-time region over which the data are collected, the sampling error can be reduced. However. the bias and distortion of the estimated rain distribution generally will remain if estimates at the high and low rain rates are not corrected. In this paper we use the TRMM PR data to investigate the behavior of 2 statistical methods the purpose of which is to estimate the rain rate over large space-time domains. Examination of large-scale rain characteristics provides a useful starting point. The high correlation between the mean and standard deviation of rain rate implies that the conditional distribution of this quantity can be approximated by a one-parameter distribution. This property is used to explore the behavior of the area-time-integral (ATI) methods where fractional area above a threshold is related to the mean rain rate. In the usual application of the ATI method a correlation is established between these quantities. However, if a particular form of the rain rate distribution is assumed and if the ratio of the mean to standard deviation is known, then not only the mean but the full distribution can be extracted from a measurement of fractional area above a threshold. The second method is an extension of this idea where the distribution is estimated from data over a range of rain rates chosen in an intermediate range where the effects of attenuation and poor sensitivity can be neglected. The advantage of estimating the distribution itself rather than the mean value is that it yields the fraction of rain contributed by

  2. A novel model of node location service based on wireless sensor networks and statistical method

    NASA Astrophysics Data System (ADS)

    Lai, Xin; Li, Jun; Li, Xiangdong; Wu, Nan

    2010-04-01

    The real-time multi-hop location system (RMLS) is a kind of service systems with a great potential in the distributed applications. The RMLS provides the precise positioning information of each node relative to one or more beacon node(s); and their absolute positions can be determined from the information. This paper study a new positioning model based on the RMLS and it applies a statistical method to increase the location's precision and enhance the robustness of a time-of-arrive(TOA)-based location system. This model has the advantage to fix the errors caused from the non-line-of-sight (NLOS) and multi-path effect (MPE); and it could be used to provide a reliable and stable location-based service for the applications, such as the scenes of an emergent logistics management and a disaster-relief emergent positioning.

  3. A study of turbulent flow between parallel plates by a statistical method

    NASA Technical Reports Server (NTRS)

    Srinivasan, R.; Giddens, D. P.; Bangert, L. H.; Wu, J. C.

    1976-01-01

    Turbulent Couette flow between parallel plates was studied from a statistical mechanics approach utilizing a model equation, similar to the Boltzmann equation of kinetic theory, which was proposed by Lundgren from the velocity distribution of fluid elements. Solutions to this equation are obtained numerically, employing the discrete ordinate method and finite differences. Two types of boundary conditions on the distribution function are considered, and the results of the calculations are compared to available experimental data. The research establishes that Lundgren's equation provides a very good description of turbulence for the flow situation considered and that it offers an analytical tool for further study of more complex turbulent flows. The present work also indicates that modelling of the boundary conditions is an area where further study is required.

  4. Statistically Qualified Neuro-Analytic system and Method for Process Monitoring

    SciTech Connect

    Vilim, Richard B.; Garcia, Humberto E.; Chen, Frederick W.

    1998-11-04

    An apparatus and method for monitoring a process involves development and application of a statistically qualified neuro-analytic (SQNA) model to accurately and reliably identify process change. The development of the SQNA model is accomplished in two steps: deterministic model adaption and stochastic model adaptation. Deterministic model adaption involves formulating an analytic model of the process representing known process characteristics,augmenting the analytic model with a neural network that captures unknown process characteristics, and training the resulting neuro-analytic model by adjusting the neural network weights according to a unique scaled equation emor minimization technique. Stochastic model adaptation involves qualifying any remaining uncertainty in the trained neuro-analytic model by formulating a likelihood function, given an error propagation equation, for computing the probability that the neuro-analytic model generates measured process output. Preferably, the developed SQNA model is validated using known sequential probability ratio tests and applied to the process as an on-line monitoring system.

  5. Performance analysis of morphological component analysis (MCA) method for mammograms using some statistical features

    NASA Astrophysics Data System (ADS)

    Gardezi, Syed Jamal Safdar; Faye, Ibrahima; Kamel, Nidal; Eltoukhy, Mohamed Meselhy; Hussain, Muhammad

    2014-10-01

    Early detection of breast cancer helps reducing the mortality rates. Mammography is very useful tool in breast cancer detection. But it is very difficult to separate different morphological features in mammographic images. In this study, Morphological Component Analysis (MCA) method is used to extract different morphological aspects of mammographic images by effectively preserving the morphological characteristics of regions. MCA decomposes the mammogram into piecewise smooth part and the texture part using the Local Discrete Cosine Transform (LDCT) and Curvelet Transform via wrapping (CURVwrap). In this study, simple comparison in performance has been done using some statistical features for the original image versus the piecewise smooth part obtained from the MCA decomposition. The results show that MCA suppresses the structural noises and blood vessels from the mammogram and enhances the performance for mass detection.

  6. Statistical methods for astronomical data with upper limits. II - Correlation and regression

    NASA Technical Reports Server (NTRS)

    Isobe, T.; Feigelson, E. D.; Nelson, P. I.

    1986-01-01

    Statistical methods for calculating correlations and regressions in bivariate censored data where the dependent variable can have upper or lower limits are presented. Cox's regression and the generalization of Kendall's rank correlation coefficient provide significant levels of correlations, and the EM algorithm, under the assumption of normally distributed errors, and its nonparametric analog using the Kaplan-Meier estimator, give estimates for the slope of a regression line. Monte Carlo simulations demonstrate that survival analysis is reliable in determining correlations between luminosities at different bands. Survival analysis is applied to CO emission in infrared galaxies, X-ray emission in radio galaxies, H-alpha emission in cooling cluster cores, and radio emission in Seyfert galaxies.

  7. Statistical method to assess usual dietary intakes in the European population.

    PubMed

    Vilone, Giulia; Comiskey, Damien; Heraud, Fanny; O'Mahony, Cian

    2014-01-01

    Food consumption data are a key element of EFSA's risk assessment activities, forming the basis of dietary exposure assessment at the European level. In 2011, EFSA released the Comprehensive European Food Consumption Database, gathering consumption data from 34 national surveys representing 66,492 individuals from 22 European Union member states. Due to the different methodologies used, national survey data cannot be combined to generate European estimates of dietary exposure. This study was executed to assess how existing consumption data and the representativeness of dietary exposure and risk estimates at the European Union level can be improved by developing a 'Compiled European Food Consumption Database'. To create the database, the usual intake distributions of 589 food items representing the total diet were estimated for 36 clusters composed of subjects belonging to the same age class, gender and having a similar diet. An adapted form of the National Cancer Institute (NCI) method was used for this, with a number of important modifications. Season, body weight and whether or not the food was consumed at the weekend were used to predict the probability of consumption. A gamma distribution was found to be more suitable for modelling the distribution of food amounts in the different food groups instead of a normal distribution. These distributions were combined with food correlation matrices according to the Iman-Conover method in order to simulate 28 days of consumption for 40,000 simulated individuals. The simulated data were validated by comparing the consumption statistics of the simulated individuals and food groups with the same statistics estimated from the Comprehensive Database. The opportunities and limitations of using the simulated database for exposure assessments are described. PMID:25205439

  8. A Method for Simulating Correlated Non-Normal Systems of Statistical Equations.

    ERIC Educational Resources Information Center

    Headrick, Todd C.; Beasley, T. Mark

    Real world data often fail to meet the underlying assumptions of normal statistical theory. Many statistical procedures in the psychological and educational sciences involve models that may include a system of statistical equations with non-normal correlated variables (e.g., factor analysis, structural equation modeling, or other complex…

  9. Statistical downscaling of daily precipitation over Llobregat river basin in Catalonia (Spain) using three downscaling methods.

    NASA Astrophysics Data System (ADS)

    Ballinas, R.; Versini, P.-A.; Sempere, D.; Escaler, I.

    2009-09-01

    environmental impact studies. Downscaling methods to assess the effect of large-scale circulations on local parameters have. Statistical downscaling methods are based on the view that regional climate can be conditioned by two factors: large-scale climatic state and regional/local features. Local climate information is derived by first developing a statistical model which relates large-scale variables or "predictors" for which GCMs are trustable to regional or local surface "predictands" for which models are less skilful. The main advantage of these methods is that they are computationally inexpensive, and can be applied to outputs from different GCM experiments. Three statistical downscaling methods are applied: Analogue method, Delta Change and Direct Forcing. These methods have been used to determine daily precipitation projections at rain gauge location to study the intensity, frequency and variability of storms in a context of climate change in the Llobregat River Basin in Catalonia, Spain. This work is part of the European project "Water Change" (included in the LIFE + Environment Policy and Governance program). It deals with Medium and long term water resources modelling as a tool for planning and global change adaptation. Two stakeholders involved in the project provided the historical time series: Catalan Water Agency (ACA) and the State Meteorological Agency (AEMET).

  10. Statistical Evaluation and Improvement of Methods for Combining Random and Harmonic Loads

    NASA Technical Reports Server (NTRS)

    Brown, A. M.; McGhee, D. S.

    2003-01-01

    Structures in many environments experience both random and harmonic excitation. A variety of closed-form techniques has been used in the aerospace industry to combine the loads resulting from the two sources. The resulting combined loads are then used to design for both yield/ultimate strength and high- cycle fatigue capability. This Technical Publication examines the cumulative distribution percentiles obtained using each method by integrating the joint probability density function of the sine and random components. A new Microsoft Excel spreadsheet macro that links with the software program Mathematica to calculate the combined value corresponding to any desired percentile is then presented along with a curve tit to this value. Another Excel macro that calculates the combination using Monte Carlo simulation is shown. Unlike the traditional techniques. these methods quantify the calculated load value with a consistent percentile. Using either of the presented methods can be extremely valuable in probabilistic design, which requires a statistical characterization of the loading. Additionally, since the CDF at high probability levels is very flat, the design value is extremely sensitive to the predetermined percentile; therefore, applying the new techniques can substantially lower the design loading without losing any of the identified structural reliability.

  11. A Review of the Statistical and Quantitative Methods Used to Study Alcohol-Attributable Crime

    PubMed Central

    Fitterer, Jessica L.; Nelson, Trisalyn A.

    2015-01-01

    Modelling the relationship between alcohol consumption and crime generates new knowledge for crime prevention strategies. Advances in data, particularly data with spatial and temporal attributes, have led to a growing suite of applied methods for modelling. In support of alcohol and crime researchers we synthesized and critiqued existing methods of spatially and quantitatively modelling the effects of alcohol exposure on crime to aid method selection, and identify new opportunities for analysis strategies. We searched the alcohol-crime literature from 1950 to January 2014. Analyses that statistically evaluated or mapped the association between alcohol and crime were included. For modelling purposes, crime data were most often derived from generalized police reports, aggregated to large spatial units such as census tracts or postal codes, and standardized by residential population data. Sixty-eight of the 90 selected studies included geospatial data of which 48 used cross-sectional datasets. Regression was the prominent modelling choice (n = 78) though dependent on data many variations existed. There are opportunities to improve information for alcohol-attributable crime prevention by using alternative population data to standardize crime rates, sourcing crime information from non-traditional platforms (social media), increasing the number of panel studies, and conducting analysis at the local level (neighbourhood, block, or point). Due to the spatio-temporal advances in crime data, we expect a continued uptake of flexible Bayesian hierarchical modelling, a greater inclusion of spatial-temporal point pattern analysis, and shift toward prospective (forecast) modelling over small areas (e.g., blocks). PMID:26418016

  12. Statistical method for prediction of gait kinematics with Gaussian process regression.

    PubMed

    Yun, Youngmok; Kim, Hyun-Chul; Shin, Sung Yul; Lee, Junwon; Deshpande, Ashish D; Kim, Changhwan

    2014-01-01

    We propose a novel methodology for predicting human gait pattern kinematics based on a statistical and stochastic approach using a method called Gaussian process regression (GPR). We selected 14 body parameters that significantly affect the gait pattern and 14 joint motions that represent gait kinematics. The body parameter and gait kinematics data were recorded from 113 subjects by anthropometric measurements and a motion capture system. We generated a regression model with GPR for gait pattern prediction and built a stochastic function mapping from body parameters to gait kinematics based on the database and GPR, and validated the model with a cross validation method. The function can not only produce trajectories for the joint motions associated with gait kinematics, but can also estimate the associated uncertainties. Our approach results in a novel, low-cost and subject-specific method for predicting gait kinematics with only the subject's body parameters as the necessary input, and also enables a comprehensive understanding of the correlation and uncertainty between body parameters and gait kinematics. PMID:24211221

  13. GBStools: A Statistical Method for Estimating Allelic Dropout in Reduced Representation Sequencing Data.

    PubMed

    Cooke, Thomas F; Yee, Muh-Ching; Muzzio, Marina; Sockell, Alexandra; Bell, Ryan; Cornejo, Omar E; Kelley, Joanna L; Bailliet, Graciela; Bravi, Claudio M; Bustamante, Carlos D; Kenny, Eimear E

    2016-02-01

    Reduced representation sequencing methods such as genotyping-by-sequencing (GBS) enable low-cost measurement of genetic variation without the need for a reference genome assembly. These methods are widely used in genetic mapping and population genetics studies, especially with non-model organisms. Variant calling error rates, however, are higher in GBS than in standard sequencing, in particular due to restriction site polymorphisms, and few computational tools exist that specifically model and correct these errors. We developed a statistical method to remove errors caused by restriction site polymorphisms, implemented in the software package GBStools. We evaluated it in several simulated data sets, varying in number of samples, mean coverage and population mutation rate, and in two empirical human data sets (N = 8 and N = 63 samples). In our simulations, GBStools improved genotype accuracy more than commonly used filters such as Hardy-Weinberg equilibrium p-values. GBStools is most effective at removing genotype errors in data sets over 100 samples when coverage is 40X or higher, and the improvement is most pronounced in species with high genomic diversity. We also demonstrate the utility of GBS and GBStools for human population genetic inference in Argentine populations and reveal widely varying individual ancestry proportions and an excess of singletons, consistent with recent population growth. PMID:26828719

  14. GBStools: A Statistical Method for Estimating Allelic Dropout in Reduced Representation Sequencing Data

    PubMed Central

    Cooke, Thomas F.; Yee, Muh-Ching; Muzzio, Marina; Sockell, Alexandra; Bell, Ryan; Cornejo, Omar E.; Kelley, Joanna L.; Bailliet, Graciela; Bravi, Claudio M.; Bustamante, Carlos D.; Kenny, Eimear E.

    2016-01-01

    Reduced representation sequencing methods such as genotyping-by-sequencing (GBS) enable low-cost measurement of genetic variation without the need for a reference genome assembly. These methods are widely used in genetic mapping and population genetics studies, especially with non-model organisms. Variant calling error rates, however, are higher in GBS than in standard sequencing, in particular due to restriction site polymorphisms, and few computational tools exist that specifically model and correct these errors. We developed a statistical method to remove errors caused by restriction site polymorphisms, implemented in the software package GBStools. We evaluated it in several simulated data sets, varying in number of samples, mean coverage and population mutation rate, and in two empirical human data sets (N = 8 and N = 63 samples). In our simulations, GBStools improved genotype accuracy more than commonly used filters such as Hardy-Weinberg equilibrium p-values. GBStools is most effective at removing genotype errors in data sets over 100 samples when coverage is 40X or higher, and the improvement is most pronounced in species with high genomic diversity. We also demonstrate the utility of GBS and GBStools for human population genetic inference in Argentine populations and reveal widely varying individual ancestry proportions and an excess of singletons, consistent with recent population growth. PMID:26828719

  15. Statistical Comparison and Improvement of Methods for Combining Random and Harmonic Loads

    NASA Technical Reports Server (NTRS)

    Brown, Andrew M.; McGhee, David S.

    2004-01-01

    Structures in many environments experience both random and harmonic excitation. A variety of closed-form techniques has been used in the aerospace industry to combine the loads resulting from the two sources. The resulting combined loads are then used to design for both yield ultimate strength and high cycle fatigue capability. This paper examines the cumulative distribution function (CDF) percentiles obtained using each method by integrating the joint probability density function of the sine and random components. A new Microsoft Excel spreadsheet macro that links with the software program Mathematics is then used to calculate the combined value corresponding to any desired percentile along with a curve fit to this value. Another Excel macro is used to calculate the combination using a Monte Carlo simulation. Unlike the traditional techniques, these methods quantify the calculated load value with a Consistent percentile. Using either of the presented methods can be extremely valuable in probabilistic design, which requires a statistical characterization of the loading. Also, since the CDF at high probability levels is very flat, the design value is extremely sensitive to the predetermined percentile; therefore, applying the new techniques can lower the design loading substantially without losing any of the identified structural reliability.

  16. Statistical Evaluation and Improvement of Methods for Combining Random and Harmonic Loads

    NASA Astrophysics Data System (ADS)

    Brown, A. M.; McGhee, D. S.

    2003-02-01

    Structures in many environments experience both random and harmonic excitation. A variety of closed-form techniques has been used in the aerospace industry to combine the loads resulting from the two sources. The resulting combined loads are then used to design for both yield/ultimate strength and high- cycle fatigue capability. This Technical Publication examines the cumulative distribution percentiles obtained using each method by integrating the joint probability density function of the sine and random components. A new Microsoft Excel spreadsheet macro that links with the software program Mathematica to calculate the combined value corresponding to any desired percentile is then presented along with a curve tit to this value. Another Excel macro that calculates the combination using Monte Carlo simulation is shown. Unlike the traditional techniques. these methods quantify the calculated load value with a consistent percentile. Using either of the presented methods can be extremely valuable in probabilistic design, which requires a statistical characterization of the loading. Additionally, since the CDF at high probability levels is very flat, the design value is extremely sensitive to the predetermined percentile; therefore, applying the new techniques can substantially lower the design loading without losing any of the identified structural reliability.

  17. Statistical properties of polarization image and despeckling method by multiresolution block-matching 3D filter

    NASA Astrophysics Data System (ADS)

    Wen, D. H.; Jiang, Y. S.; Zhang, Y. Z.; Gao, Q.

    2014-03-01

    The theoretical and experimental investigations on the polarization imagery system of speckle statistical characteristics and speckle removing method are researched. A method to obtain two images encoded by polarization degree with a single measurement process is proposed. A theoretical model for polarization imagery system on Müller matrix is proposed. According to modern charge coupled device (CCD) imaging characteristics, speckles are divided into two kinds, namely small speckle and big speckle. Based on this model, a speckle reduction algorithm based on a dual-tree complex wavelet transform (DTCWT) and blockmatching 3D filter (BM3D) is proposed (DTBM3D). Original laser image data transformed by logarithmic compression is decomposed by DTCWT into approximation and detail subbands. Bilateral filtering is applied to the approximation subbands, and a suited BM3D filter is applied to the detail subbands. The despeckling results show that contrast improvement index and edge preserve index outperform those of traditional methods. The researches have important reference value in research of speckle noise level and removing speckle noise.

  18. Statistical analysis to assess automated level of suspicion scoring methods in breast ultrasound

    NASA Astrophysics Data System (ADS)

    Galperin, Michael

    2003-05-01

    A well-defined rule-based system has been developed for scoring 0-5 the Level of Suspicion (LOS) based on qualitative lexicon describing the ultrasound appearance of breast lesion. The purposes of the research are to asses and select one of the automated LOS scoring quantitative methods developed during preliminary studies in benign biopsies reduction. The study has used Computer Aided Imaging System (CAIS) to improve the uniformity and accuracy of applying the LOS scheme by automatically detecting, analyzing and comparing breast masses. The overall goal is to reduce biopsies on the masses with lower levels of suspicion, rather that increasing the accuracy of diagnosis of cancers (will require biopsy anyway). On complex cysts and fibroadenoma cases experienced radiologists were up to 50% less certain in true negatives than CAIS. Full correlation analysis was applied to determine which of the proposed LOS quantification methods serves CAIS accuracy the best. This paper presents current results of applying statistical analysis for automated LOS scoring quantification for breast masses with known biopsy results. It was found that First Order Ranking method yielded most the accurate results. The CAIS system (Image Companion, Data Companion software) is developed by Almen Laboratories and was used to achieve the results.

  19. Novel Application of Statistical Methods to Identify New Urinary Incontinence Risk Factors

    PubMed Central

    Ogunyemi, Theophilus O.; Siadat, Mohammad-Reza; Arslanturk, Suzan; Killinger, Kim A.; Diokno, Ananias C.

    2012-01-01

    Longitudinal data for studying urinary incontinence (UI) risk factors are rare. Data from one study, the hallmark Medical, Epidemiological, and Social Aspects of Aging (MESA), have been analyzed in the past; however, repeated measures analyses that are crucial for analyzing longitudinal data have not been applied. We tested a novel application of statistical methods to identify UI risk factors in older women. MESA data were collected at baseline and yearly from a sample of 1955 men and women in the community. Only women responding to the 762 baseline and 559 follow-up questions at one year in each respective survey were examined. To test their utility in mining large data sets, and as a preliminary step to creating a predictive index for developing UI, logistic regression, generalized estimating equations (GEEs), and proportional hazard regression (PHREG) methods were used on the existing MESA data. The GEE and PHREG combination identified 15 significant risk factors associated with developing UI out of which six of them, namely, urinary frequency, urgency, any urine loss, urine loss after emptying, subject's anticipation, and doctor's proactivity, are found most highly significant by both methods. These six factors are potential candidates for constructing a future UI predictive index. PMID:23193394

  20. Computed statistics at streamgages, and methods for estimating low-flow frequency statistics and development of regional regression equations for estimating low-flow frequency statistics at ungaged locations in Missouri

    USGS Publications Warehouse

    Southard, Rodney E.

    2013-01-01

    The weather and precipitation patterns in Missouri vary considerably from year to year. In 2008, the statewide average rainfall was 57.34 inches and in 2012, the statewide average rainfall was 30.64 inches. This variability in precipitation and resulting streamflow in Missouri underlies the necessity for water managers and users to have reliable streamflow statistics and a means to compute select statistics at ungaged locations for a better understanding of water availability. Knowledge of surface-water availability is dependent on the streamflow data that have been collected and analyzed by the U.S. Geological Survey for more than 100 years at approximately 350 streamgages throughout Missouri. The U.S. Geological Survey, in cooperation with the Missouri Department of Natural Resources, computed streamflow statistics at streamgages through the 2010 water year, defined periods of drought and defined methods to estimate streamflow statistics at ungaged locations, and developed regional regression equations to compute selected streamflow statistics at ungaged locations. Streamflow statistics and flow durations were computed for 532 streamgages in Missouri and in neighboring States of Missouri. For streamgages with more than 10 years of record, Kendall’s tau was computed to evaluate for trends in streamflow data. If trends were detected, the variable length method was used to define the period of no trend. Water years were removed from the dataset from the beginning of the record for a streamgage until no trend was detected. Low-flow frequency statistics were then computed for the entire period of record and for the period of no trend if 10 or more years of record were available for each analysis. Three methods are presented for computing selected streamflow statistics at ungaged locations. The first method uses power curve equations developed for 28 selected streams in Missouri and neighboring States that have multiple streamgages on the same streams. Statistical

  1. Inferences on weather extremes and weather-related disasters: a review of statistical methods

    NASA Astrophysics Data System (ADS)

    Visser, H.; Petersen, A. C.

    2012-02-01

    The study of weather extremes and their impacts, such as weather-related disasters, plays an important role in research of climate change. Due to the great societal consequences of extremes - historically, now and in the future - the peer-reviewed literature on this theme has been growing enormously since the 1980s. Data sources have a wide origin, from century-long climate reconstructions from tree rings to relatively short (30 to 60 yr) databases with disaster statistics and human impacts. When scanning peer-reviewed literature on weather extremes and its impacts, it is noticeable that many different methods are used to make inferences. However, discussions on these methods are rare. Such discussions are important since a particular methodological choice might substantially influence the inferences made. A calculation of a return period of once in 500 yr, based on a normal distribution will deviate from that based on a Gumbel distribution. And the particular choice between a linear or a flexible trend model might influence inferences as well. In this article, a concise overview of statistical methods applied in the field of weather extremes and weather-related disasters is given. Methods have been evaluated as to stationarity assumptions, the choice for specific probability density functions (PDFs) and the availability of uncertainty information. As for stationarity assumptions, the outcome was that good testing is essential. Inferences on extremes may be wrong if data are assumed stationary while they are not. The same holds for the block-stationarity assumption. As for PDF choices it was found that often more than one PDF shape fits to the same data. From a simulation study the conclusion can be drawn that both the generalized extreme value (GEV) distribution and the log-normal PDF fit very well to a variety of indicators. The application of the normal and Gumbel distributions is more limited. As for uncertainty, it is advisable to test conclusions on extremes

  2. Combining statistical and physics-based methods for predicting induced seismic hazard during reservoir stimulation

    NASA Astrophysics Data System (ADS)

    Gischig, V. S.; Mena Cabrera, B.; Goertz-Allmann, B.; Wiemer, S.

    2012-12-01

    observed data. We demonstrate that the model can reasonably reproduce both the temporal evolution of observed event statistics, and minimally the extent of at the seismic cloud recorded during the Basel reservoir stimulation in 2006. We also argue that triggering pressure is at a realistic order of magnitude, because modeled and measured wellhead pressure curves are in good agreement. Furthermore, the model is tested against observations in a pseudo-prospective manner, and compared to the existing purely statistical forecasting methods. Finally, we use the calibrated model to explore different injection scenarios, and their consequences for seismic hazard. Translating the calibrated models with different injection scenarios into probabilistic seismic hazard allows us to qualitatively compare their effects on the probability of occurrence of a hazardous event. Our modeling strategy and statistical testing procedure forms a test-bed that can be used to investigate the forecasting capabilities of future models developed towards higher physical complexity.

  3. Statistical downscaling of precipitation using local regression and high accuracy surface modeling method

    NASA Astrophysics Data System (ADS)

    Zhao, Na; Yue, Tianxiang; Zhou, Xun; Zhao, Mingwei; Liu, Yu; Du, Zhengping; Zhang, Lili

    2016-03-01

    Downscaling precipitation is required in local scale climate impact studies. In this paper, a statistical downscaling scheme was presented with a combination of geographically weighted regression (GWR) model and a recently developed method, high accuracy surface modeling method (HASM). This proposed method was compared with another downscaling method using the Coupled Model Intercomparison Project Phase 5 (CMIP5) database and ground-based data from 732 stations across China for the period 1976-2005. The residual which was produced by GWR was modified by comparing different interpolators including HASM, Kriging, inverse distance weighted method (IDW), and Spline. The spatial downscaling from 1° to 1-km grids for period 1976-2005 and future scenarios was achieved by using the proposed downscaling method. The prediction accuracy was assessed at two separate validation sites throughout China and Jiangxi Province on both annual and seasonal scales, with the root mean square error (RMSE), mean relative error (MRE), and mean absolute error (MAE). The results indicate that the developed model in this study outperforms the method that builds transfer function using the gauge values. There is a large improvement in the results when using a residual correction with meteorological station observations. In comparison with other three classical interpolators, HASM shows better performance in modifying the residual produced by local regression method. The success of the developed technique lies in the effective use of the datasets and the modification process of the residual by using HASM. The results from the future climate scenarios show that precipitation exhibits overall increasing trend from T1 (2011-2040) to T2 (2041-2070) and T2 to T3 (2071-2100) in RCP2.6, RCP4.5, and RCP8.5 emission scenarios. The most significant increase occurs in RCP8.5 from T2 to T3, while the lowest increase is found in RCP2.6 from T2 to T3, increased by 47.11 and 2.12 mm, respectively.

  4. Indoor Soiling Method and Outdoor Statistical Risk Analysis of Photovoltaic Power Plants

    NASA Astrophysics Data System (ADS)

    Rajasekar, Vidyashree

    This is a two-part thesis. Part 1 presents an approach for working towards the development of a standardized artificial soiling method for laminated photovoltaic (PV) cells or mini-modules. Construction of an artificial chamber to maintain controlled environmental conditions and components/chemicals used in artificial soil formulation is briefly explained. Both poly-Si mini-modules and a single cell mono-Si coupons were soiled and characterization tests such as I-V, reflectance and quantum efficiency (QE) were carried out on both soiled, and cleaned coupons. From the results obtained, poly-Si mini-modules proved to be a good measure of soil uniformity, as any non-uniformity present would not result in a smooth curve during I-V measurements. The challenges faced while executing reflectance and QE characterization tests on poly-Si due to smaller size cells was eliminated on the mono-Si coupons with large cells to obtain highly repeatable measurements. This study indicates that the reflectance measurements between 600-700 nm wavelengths can be used as a direct measure of soil density on the modules. Part 2 determines the most dominant failure modes of field aged PV modules using experimental data obtained in the field and statistical analysis, FMECA (Failure Mode, Effect, and Criticality Analysis). The failure and degradation modes of about 744 poly-Si glass/polymer frameless modules fielded for 18 years under the cold-dry climate of New York was evaluated. Defect chart, degradation rates (both string and module levels) and safety map were generated using the field measured data. A statistical reliability tool, FMECA that uses Risk Priority Number (RPN) is used to determine the dominant failure or degradation modes in the strings and modules by means of ranking and prioritizing the modes. This study on PV power plants considers all the failure and degradation modes from both safety and performance perspectives. The indoor and outdoor soiling studies were jointly

  5. Uncertainty analysis of statistical downscaling methods using Canadian Global Climate Model predictors

    NASA Astrophysics Data System (ADS)

    Khan, Mohammad Sajjad; Coulibaly, Paulin; Dibike, Yonas

    2006-09-01

    Three downscaling models, namely the Statistical Down-Scaling Model (SDSM), the Long Ashton Research Station Weather Generator (LARS-WG) model and an artificial neural network (ANN) model, have been compared in terms of various uncertainty attributes exhibited in their downscaled results of daily precipitation, daily maximum and minimum temperature. The uncertainty attributes are described by the model errors and the 95% confidence intervals in the estimates of means and variances of downscaled data. The significance of those errors has been examined by suitable statistical tests at the 95% confidence level. The 95% confidence intervals in the estimates of means and variances of downscaled data have been estimated using the bootstrapping method and compared with the observed data. The study has been carried out using 40 years of observed and downscaled daily precipitation data and daily maximum and minimum temperature data, starting from 1961 to 2000. In all the downscaling experiments, the simulated predictors of the Canadian Global Climate Model (CGCM1) have been used. The uncertainty assessment results indicate that, in daily precipitation downscaling, the LARS-WG model errors are significant at the 95% confidence level only in a very few months, the SDSM errors are significant in some months, and the ANN model errors are significant in almost all months of the year. In downscaling daily maximum and minimum temperature, the performance of all three models is similar in terms of model errors evaluation at the 95% confidence level. But, according to the evaluation of variability and uncertainty in the estimates of means and variances of downscaled precipitation and temperature, the performances of the LARS-WG model and the SDSM are almost similar, whereas the ANN model performance is found to be poor in that consideration. Further assessment of those models, in terms of skewness and average dry-spell length comparison between observed and downscaled daily

  6. Oil and Gas on Indian Reservations: Statistical Methods Help to Establish Value for Royalty Purposes

    ERIC Educational Resources Information Center

    Fowler, Mary S.; Kadane, Joseph B.

    2006-01-01

    Part of the history of oil and gas development on Indian reservations concerns potential underpayment of royalties due to under-valuation of production by oil companies. This paper discusses a model used by the Shoshone and Arapaho tribes in a lawsuit against the Federal government, claiming the Government failed to collect adequate royalties.…

  7. How to choose the right statistical software?-a method increasing the post-purchase satisfaction.

    PubMed

    Cavaliere, Roberto

    2015-12-01

    Nowadays, we live in the "data era" where the use of statistical or data analysis software is inevitable, in any research field. This means that the choice of the right software tool or platform is a strategic issue for a research department. Nevertheless, in many cases decision makers do not pay the right attention to a comprehensive and appropriate evaluation of what the market offers. Indeed, the choice still depends on few factors like, for instance, researcher's personal inclination, e.g., which software have been used at the university or is already known. This is not wrong in principle, but in some cases it's not enough at all and might lead to a "dead end" situation, typically after months or years of investments already done on the wrong software. This article, far from being a full and complete guide to statistical software evaluation, aims to illustrate some key points of the decision process and introduce an extended range of factors which can help to undertake the right choice, at least in potential. There is not enough literature about that topic, most of the time underestimated, both in the traditional literature and even in the so called "gray literature", even if some documents or short pages can be found online. Anyhow, it seems there is not a common and known standpoint about the process of software evaluation from the final user perspective. We suggests a multi-factor analysis leading to an evaluation matrix tool, to be intended as a flexible and customizable tool, aimed to provide a clearer picture of the software alternatives available, not in abstract but related to the researcher's own context and needs. This method is a result of about twenty years of experience of the author in the field of evaluating and using technical-computing software and partially arises from a research made about such topics as part of a project funded by European Commission under the Lifelong Learning Programme 2011. PMID:26793368

  8. PNS and statistical experiments simulation in subcritical systems using Monte-Carlo method on example of Yalina-Thermal assembly

    NASA Astrophysics Data System (ADS)

    Sadovich, Sergey; Talamo, A.; Burnos, V.; Kiyavitskaya, H.; Fokov, Yu.

    2014-06-01

    In subcritical systems driven by an external neutron source, the experimental methods based on pulsed neutron source and statistical techniques play an important role for reactivity measurement. Simulation of these methods is very time-consumed procedure. For simulations in Monte-Carlo programs several improvements for neutronic calculations have been made. This paper introduces a new method for simulation PNS and statistical measurements. In this method all events occurred in the detector during simulation are stored in a file using PTRAC feature in the MCNP. After that with a special code (or post-processing) PNS and statistical methods can be simulated. Additionally different shapes of neutron pulses and its lengths as well as dead time of detectors can be included into simulation. The methods described above were tested on subcritical assembly Yalina-Thermal, located in Joint Institute for Power and Nuclear Research SOSNY, Minsk, Belarus. A good agreement between experimental and simulated results was shown.

  9. Energy Production Calculations with Field Flow Models and Windspeed Predictions with Statistical Methods

    NASA Astrophysics Data System (ADS)

    Rüstemoǧlu, Sevinç; Barutçu, Burak; Sibel Menteş, Å.ž.

    2010-05-01

    The continuous usage of fossil fuels as primary energy source is the reason of the emission of CO and powerless economy of the country affected by the great flactuations in the unit price of energy sources. In recent years, developments in wind energy sector and the supporting new renewable energy policies of the countries allow the new wind farm owners and the firms who expect to be an owner to consider and invest on the renewable sources. In this study, the annual production of the turbines with 1.8 kW and 30 kW which are available for Istanbul Technical University in Energy Institute is calculated by Wasp and WindPro Field Flow Models and the wind characteristics of the area are analysed. The meteorological data used in calculation includes the period between 02.March.2000 and 31.May.2004 and is taken from the meteorological mast ( ) in Istanbul Technical University's campus area. The measurement data is taken from 2 m and 10 m heights with hourly means. The topography, roughness classes and shelter effects are defined in the models to make accurate extrapolation to the turbine sites. As an advantage, the region is nearly 3.5 km close to the Istanbul Bosphorous but as it can be seen from the Wasp and WindPro Model Results, the Bosphorous effect is interrupted by the new buildings and hight forestry. The shelter effect of these high buildings have a great influence on the wind flow and decrease the high wind energy potential which is produced by the Bosphorous effect. This study, which determines wind characteristics and expected annual production, is important for this Project Site and therefore gains importance before the construction of wind energy system. However, when the system is operating, developing the energy management skills, forecasting the wind speed and direction will become important. At this point, three statistical models which are Kalman Fitler, AR Model and Neural Networks models are used to determine the success of each method for correct

  10. Methods of learning in statistical education: Design and analysis of a randomized trial

    NASA Astrophysics Data System (ADS)

    Boyd, Felicity Turner

    Background. Recent psychological and technological advances suggest that active learning may enhance understanding and retention of statistical principles. A randomized trial was designed to evaluate the addition of innovative instructional methods within didactic biostatistics courses for public health professionals. Aims. The primary objectives were to evaluate and compare the addition of two active learning methods (cooperative and internet) on students' performance; assess their impact on performance after adjusting for differences in students' learning style; and examine the influence of learning style on trial participation. Methods. Consenting students enrolled in a graduate introductory biostatistics course were randomized to cooperative learning, internet learning, or control after completing a pretest survey. The cooperative learning group participated in eight small group active learning sessions on key statistical concepts, while the internet learning group accessed interactive mini-applications on the same concepts. Controls received no intervention. Students completed evaluations after each session and a post-test survey. Study outcome was performance quantified by examination scores. Intervention effects were analyzed by generalized linear models using intent-to-treat analysis and marginal structural models accounting for reported participation. Results. Of 376 enrolled students, 265 (70%) consented to randomization; 69, 100, and 96 students were randomized to the cooperative, internet, and control groups, respectively. Intent-to-treat analysis showed no differences between study groups; however, 51% of students in the intervention groups had dropped out after the second session. After accounting for reported participation, expected examination scores were 2.6 points higher (of 100 points) after completing one cooperative learning session (95% CI: 0.3, 4.9) and 2.4 points higher after one internet learning session (95% CI: 0.0, 4.7), versus

  11. Bayesian Analysis of Two Stellar Populations in Galactic Globular Clusters. I. Statistical and Computational Methods

    NASA Astrophysics Data System (ADS)

    Stenning, D. C.; Wagner-Kaiser, R.; Robinson, E.; van Dyk, D. A.; von Hippel, T.; Sarajedini, A.; Stein, N.

    2016-07-01

    We develop a Bayesian model for globular clusters composed of multiple stellar populations, extending earlier statistical models for open clusters composed of simple (single) stellar populations. Specifically, we model globular clusters with two populations that differ in helium abundance. Our model assumes a hierarchical structuring of the parameters in which physical properties—age, metallicity, helium abundance, distance, absorption, and initial mass—are common to (i) the cluster as a whole or to (ii) individual populations within a cluster, or are unique to (iii) individual stars. An adaptive Markov chain Monte Carlo (MCMC) algorithm is devised for model fitting that greatly improves convergence relative to its precursor non-adaptive MCMC algorithm. Our model and computational tools are incorporated into an open-source software suite known as BASE-9. We use numerical studies to demonstrate that our method can recover parameters of two-population clusters, and also show how model misspecification can potentially be identified. As a proof of concept, we analyze the two stellar populations of globular cluster NGC 5272 using our model and methods. (BASE-9 is available from GitHub: https://github.com/argiopetech/base/releases).

  12. Evaluation of xenobiotic impact on urban receiving waters by means of statistical methods.

    PubMed

    Musolff, A; Leschik, S; Schafmeister, M-T; Reinstorf, F; Strauch, G; Krieg, R; Schirmer, M

    2010-01-01

    Xenobiotics in urban receiving waters are an emerging problem. A sound knowledge of xenobiotic input, distribution and fate in the aquatic environment is a prerequisite for risk assessments. Methods to assess the impact of xenobiotics on urban receiving waters should address the diverse characteristics of the target compounds and the spatiotemporal variability of concentrations. Here, we present results from a one-year-monitoring program concerning concentrations of pharmaceuticals, additives from personal care products and industrial chemicals in an urban drainage catchment in untreated and treated wastewater, surface water and groundwater. Univariate and multivariate statistical methods were applied to characterize the xenobiotic concentrations. Correlation and principal component analysis revealed a pronounced pattern of xenobiotics in the surface water samples. The concentrations of several xenobiotics were characterized by a negative proportionality to the water temperature. Therefore, seasonal attenuation is assumed to be a major process influencing the measured concentrations. Moreover, dilution of xenobiotics the surface water was found to significantly influence the concentrations. These two processes control more the xenobiotic occurrence in the surface water than the less pronounced concentration pattern in the wastewater sources. For the groundwater samples, we assume that foremost attenuation processes lead to the found differentiation of xenobiotics. PMID:20706016

  13. Statistical and computational methods for comparative proteomic profiling using liquid chromatography-tandem mass spectrometry.

    PubMed

    Listgarten, Jennifer; Emili, Andrew

    2005-04-01

    The combined method of LC-MS/MS is increasingly being used to explore differences in the proteomic composition of complex biological systems. The reliability and utility of such comparative protein expression profiling studies is critically dependent on an accurate and rigorous assessment of quantitative changes in the relative abundance of the myriad of proteins typically present in a biological sample such as blood or tissue. In this review, we provide an overview of key statistical and computational issues relevant to bottom-up shotgun global proteomic analysis, with an emphasis on methods that can be applied to improve the dependability of biological inferences drawn from large proteomic datasets. Focusing on a start-to-finish approach, we address the following topics: 1) low-level data processing steps, such as formation of a data matrix, filtering, and baseline subtraction to minimize noise, 2) mid-level processing steps, such as data normalization, alignment in time, peak detection, peak quantification, peak matching, and error models, to facilitate profile comparisons; and, 3) high-level processing steps such as sample classification and biomarker discovery, and related topics such as significance testing, multiple testing, and choice of feature space. We report on approaches that have recently been developed for these steps, discussing their merits and limitations, and propose areas deserving of further research. PMID:15741312

  14. A STATISTICAL METHOD FOR MEASURING THE GALACTIC POTENTIAL AND TESTING GRAVITY WITH COLD TIDAL STREAMS

    SciTech Connect

    Penarrubia, Jorge; Walker, Matthew G.

    2012-11-20

    We introduce the Minimum Entropy Method, a simple statistical technique for constraining the Milky Way gravitational potential and simultaneously testing different gravity theories directly from 6D phase-space surveys and without adopting dynamical models. We demonstrate that orbital energy distributions that are separable (i.e., independent of position) have an associated entropy that increases under wrong assumptions about the gravitational potential and/or gravity theory. Of known objects, 'cold' tidal streams from low-mass progenitors follow orbital distributions that most nearly satisfy the condition of separability. Although the orbits of tidally stripped stars are perturbed by the progenitor's self-gravity, systematic variations of the energy distribution can be quantified in terms of the cross-entropy of individual tails, giving further sensitivity to theoretical biases in the host potential. The feasibility of using the Minimum Entropy Method to test a wide range of gravity theories is illustrated by evolving restricted N-body models in a Newtonian potential and examining the changes in entropy introduced by Dirac, MONDian, and f(R) gravity modifications.

  15. Native fluorescence spectroscopy of cervical tissues: classification by different statistical methods

    NASA Astrophysics Data System (ADS)

    Ganesan, Singaravelu; Vengadesan, Nammalver; Anbupalam, Thalaimuthu; Hemamalini, Srinivasan; Aruna, Prakasa R.; Karkuzhali, P.

    2002-05-01

    Optical Spectroscopy in the diagnosis of diseases has attracted the medical community due to their minimally invasive nature. Among various optical spectroscopic techniques, native fluorescence spectroscopy has emerged as a potential tool in diagnostic oncology. However, still the reasons for the altered spectral signatures between normal and cancer tissues not yet completely understood. Recently, data reported that emission due to the alteration of some proteins is responsible for the transformation of normal in to malignant one. In this regard, the present study is aimed to characterize the native fluorescence spectroscopy of abnormal and normal cervical tissues, at 280nm excitation. From the study, it is observed that the normal and pathologically diseased cervical tissues have their peak emission around 339 and 336nm respectively with a secondary peak around 440nm. The FWHM value of emission spectra of abnormal tissues is lower than that of normal tissues. The fluorescence spectra of normal and various pathological conditions of cancerous tissues were analyzed by various empirical and statistical methods. Among various type of discriminant analysis, combination of ratio values and linear discrimination method provides better discrimination of normal from pre-malignant and malignant tissues.

  16. Feature Selection Applying Statistical and Neurofuzzy Methods to EEG-Based BCI

    PubMed Central

    Martinez-Leon, Juan-Antonio; Cano-Izquierdo, Jose-Manuel; Ibarrola, Julio

    2015-01-01

    This paper presents an investigation aimed at drastically reducing the processing burden required by motor imagery brain-computer interface (BCI) systems based on electroencephalography (EEG). In this research, the focus has moved from the channel to the feature paradigm, and a 96% reduction of the number of features required in the process has been achieved maintaining and even improving the classification success rate. This way, it is possible to build cheaper, quicker, and more portable BCI systems. The data set used was provided within the framework of BCI Competition III, which allows it to compare the presented results with the classification accuracy achieved in the contest. Furthermore, a new three-step methodology has been developed which includes a feature discriminant character calculation stage; a score, order, and selection phase; and a final feature selection step. For the first stage, both statistics method and fuzzy criteria are used. The fuzzy criteria are based on the S-dFasArt classification algorithm which has shown excellent performance in previous papers undertaking the BCI multiclass motor imagery problem. The score, order, and selection stage is used to sort the features according to their discriminant nature. Finally, both order selection and Group Method Data Handling (GMDH) approaches are used to choose the most discriminant ones. PMID:25977685

  17. Statistical modification analysis of helical planetary gears based on response surface method and Monte Carlo simulation

    NASA Astrophysics Data System (ADS)

    Zhang, Jun; Guo, Fan

    2015-11-01

    Tooth modification technique is widely used in gear industry to improve the meshing performance of gearings. However, few of the present studies on tooth modification considers the influence of inevitable random errors on gear modification effects. In order to investigate the uncertainties of tooth modification amount variations on system's dynamic behaviors of a helical planetary gears, an analytical dynamic model including tooth modification parameters is proposed to carry out a deterministic analysis on the dynamics of a helical planetary gear. The dynamic meshing forces as well as the dynamic transmission errors of the sun-planet 1 gear pair with and without tooth modifications are computed and compared to show the effectiveness of tooth modifications on gear dynamics enhancement. By using response surface method, a fitted regression model for the dynamic transmission error(DTE) fluctuations is established to quantify the relationship between modification amounts and DTE fluctuations. By shifting the inevitable random errors arousing from manufacturing and installing process to tooth modification amount variations, a statistical tooth modification model is developed and a methodology combining Monte Carlo simulation and response surface method is presented for uncertainty analysis of tooth modifications. The uncertainly analysis reveals that the system's dynamic behaviors do not obey the normal distribution rule even though the design variables are normally distributed. In addition, a deterministic modification amount will not definitely achieve an optimal result for both static and dynamic transmission error fluctuation reduction simultaneously.

  18. Spectral-Lagrangian methods for collisional models of non-equilibrium statistical states

    SciTech Connect

    Gamba, Irene M. Tharkabhushanam, Sri Harsha

    2009-04-01

    We propose a new spectral Lagrangian based deterministic solver for the non-linear Boltzmann transport equation (BTE) in d-dimensions for variable hard sphere (VHS) collision kernels with conservative or non-conservative binary interactions. The method is based on symmetries of the Fourier transform of the collision integral, where the complexity in its computation is reduced to a separate integral over the unit sphere S{sup d-1}. The conservation of moments is enforced by Lagrangian constraints. The resulting scheme, implemented in free space, is very versatile and adjusts in a very simple manner to several cases that involve energy dissipation due to local micro-reversibility (inelastic interactions) or elastic models of slowing down process. Our simulations are benchmarked with available exact self-similar solutions, exact moment equations and analytical estimates for the homogeneous Boltzmann equation, both for elastic and inelastic VHS interactions. Benchmarking of the simulations involves the selection of a time self-similar rescaling of the numerical distribution function which is performed using the continuous spectrum of the equation for Maxwell molecules as studied first in Bobylev et al. [A.V. Bobylev, C. Cercignani, G. Toscani, Proof of an asymptotic property of self-similar solutions of the Boltzmann equation for granular materials, Journal of Statistical Physics 111 (2003) 403-417] and generalized to a wide range of related models in Bobylev et al. [A.V. Bobylev, C. Cercignani, I.M. Gamba, On the self-similar asymptotics for generalized non-linear kinetic Maxwell models, Communication in Mathematical Physics, in press. URL: ()]. The method also produces accurate results in the case of inelastic diffusive Boltzmann equations for hard spheres (inelastic collisions under thermal bath), where overpopulated non-Gaussian exponential tails have been conjectured in computations by stochastic methods [T.V. Noije, M. Ernst

  19. Statistical Track-Before-Detect Methods Applied to Faint Optical Observations of Resident Space Objects

    NASA Astrophysics Data System (ADS)

    Fujimoto, K.; Yanagisawa, T.; Uetsuhara, M.

    Automated detection and tracking of faint objects in optical, or bearing-only, sensor imagery is a topic of immense interest in space surveillance. Robust methods in this realm will lead to better space situational awareness (SSA) while reducing the cost of sensors and optics. They are especially relevant in the search for high area-to-mass ratio (HAMR) objects, as their apparent brightness can change significantly over time. A track-before-detect (TBD) approach has been shown to be suitable for faint, low signal-to-noise ratio (SNR) images of resident space objects (RSOs). TBD does not rely upon the extraction of feature points within the image based on some thresholding criteria, but rather directly takes as input the intensity information from the image file. Not only is all of the available information from the image used, TBD avoids the computational intractability of the conventional feature-based line detection (i.e., "string of pearls") approach to track detection for low SNR data. Implementation of TBD rooted in finite set statistics (FISST) theory has been proposed recently by Vo, et al. Compared to other TBD methods applied so far to SSA, such as the stacking method or multi-pass multi-period denoising, the FISST approach is statistically rigorous and has been shown to be more computationally efficient, thus paving the path toward on-line processing. In this paper, we intend to apply a multi-Bernoulli filter to actual CCD imagery of RSOs. The multi-Bernoulli filter can explicitly account for the birth and death of multiple targets in a measurement arc. TBD is achieved via a sequential Monte Carlo implementation. Preliminary results with simulated single-target data indicate that a Bernoulli filter can successfully track and detect objects with measurement SNR as low as 2.4. Although the advent of fast-cadence scientific CMOS sensors have made the automation of faint object detection a realistic goal, it is nonetheless a difficult goal, as measurements

  20. Evaluation of Oceanic Transport Statistics By Use of Transient Tracers and Bayesian Methods

    NASA Astrophysics Data System (ADS)

    Trossman, D. S.; Thompson, L.; Mecking, S.; Bryan, F.; Peacock, S.

    2013-12-01

    Key variables that quantify the time scales over which atmospheric signals penetrate into the oceanic interior and their uncertainties are computed using Bayesian methods and transient tracers from both models and observations. First, the mean residence times, subduction rates, and formation rates of Subtropical Mode Water (STMW) and Subpolar Mode Water (SPMW) in the North Atlantic and Subantarctic Mode Water (SAMW) in the Southern Ocean are estimated by combining a model and observations of chlorofluorocarbon-11 (CFC-11) via Bayesian Model Averaging (BMA), statistical technique that weights model estimates according to how close they agree with observations. Second, a Bayesian method is presented to find two oceanic transport parameters associated with the age distribution of ocean waters, the transit-time distribution (TTD), by combining an eddying global ocean model's estimate of the TTD with hydrographic observations of CFC-11, temperature, and salinity. Uncertainties associated with objectively mapping irregularly spaced bottle data are quantified by making use of a thin-plate spline and then propagated via the two Bayesian techniques. It is found that the subduction of STMW, SPMW, and SAMW is mostly an advective process, but up to about one-third of STMW subduction likely owes to non-advective processes. Also, while the formation of STMW is mostly due to subduction, the formation of SPMW is mostly due to other processes. About half of the formation of SAMW is due to subduction and half is due to other processes. A combination of air-sea flux, acting on relatively short time scales, and turbulent mixing, acting on a wide range of time scales, is likely the dominant SPMW erosion mechanism. Air-sea flux is likely responsible for most STMW erosion, and turbulent mixing is likely responsible for most SAMW erosion. Two oceanic transport parameters, the mean age of a water parcel and the half-variance associated with the TTD, estimated using the model's tracers as

  1. Machine learning and statistical methods for the prediction of maximal oxygen uptake: recent advances.

    PubMed

    Abut, Fatih; Akay, Mehmet Fatih

    2015-01-01

    Maximal oxygen uptake (VO2max) indicates how many milliliters of oxygen the body can consume in a state of intense exercise per minute. VO2max plays an important role in both sport and medical sciences for different purposes, such as indicating the endurance capacity of athletes or serving as a metric in estimating the disease risk of a person. In general, the direct measurement of VO2max provides the most accurate assessment of aerobic power. However, despite a high level of accuracy, practical limitations associated with the direct measurement of VO2max, such as the requirement of expensive and sophisticated laboratory equipment or trained staff, have led to the development of various regression models for predicting VO2max. Consequently, a lot of studies have been conducted in the last years to predict VO2max of various target audiences, ranging from soccer athletes, nonexpert swimmers, cross-country skiers to healthy-fit adults, teenagers, and children. Numerous prediction models have been developed using different sets of predictor variables and a variety of machine learning and statistical methods, including support vector machine, multilayer perceptron, general regression neural network, and multiple linear regression. The purpose of this study is to give a detailed overview about the data-driven modeling studies for the prediction of VO2max conducted in recent years and to compare the performance of various VO2max prediction models reported in related literature in terms of two well-known metrics, namely, multiple correlation coefficient (R) and standard error of estimate. The survey results reveal that with respect to regression methods used to develop prediction models, support vector machine, in general, shows better performance than other methods, whereas multiple linear regression exhibits the worst performance. PMID:26346869

  2. Optimization of the Analogs method in the framework of statistical weather forecasting in the Swiss Alps

    NASA Astrophysics Data System (ADS)

    Horton, P.; Jaboyedoff, M.; Obled, C.; Metzger, R.

    2010-09-01

    Probabilistic quantitative precipitation forecasts (PQPF) by means of the Analogs method is being developed for the Swiss Alps. The goal is to provide a statistical forecast to the MINERVE project, which aims at reducing the flood peaks of the Rhône river by means of water retention in dams. Their operation requires precipitation forecasts for several days ahead. This downscaling approach allows bypassing the modeling of physical processes generating the precipitation. Thus, it should extend the information on which decision makers build up their choices, when considered in parallel to physically based numerical prediction model (NWP) outputs processed by MeteoSwiss. The Analogs method is a simple concept: given a rainfall archive and a meteorological archive containing a large amount of candidate predictors, the goal is to find the best set of predictors and of parameters ( time and spatial windows, number of analogs, weightings, etc…) which relates synoptic information to local rainfall. This makes the model opened to improvements, with almost endless possibilities that are impossible to explore manually. Thus, an optimizer based on the Nelder-Mead method was implemented to proceed to an automatic parameter calibration. This allows to introduce new concepts and to remove some limitations that existed for the simplification of the manual calibration. Results are in good agreement with known case studies and consistent with the underlying physics.. The different regions in the Swiss Alps are sensitive to distinct meteorological situations. As a consequence, the best predictors vary from a sub-region to another. This was observed for various parts of the alpine Rhône catchment that are characterized by a strong orographic effect under specific circumstances. The spatial windows of the selected predictor highlight the best location where predictors must be compared to downscale at best the precipitation of a given sub-region. It was found that those locations

  3. A physical-based statistical method for modeling ocean wave heights

    NASA Astrophysics Data System (ADS)

    Casas-Prat, Mercè; Wang, Xiaolan L.; Sierra, Joan P.

    2014-01-01

    This study proposes a computationally inexpensive statistical method for modeling ocean wave heights, focusing particularly on modeling wave heights in near-shore areas. A multiple linear regression is used to predict significant wave heights (Hs) using predictors derived from the sea level pressure (SLP) field, including the use of squared SLP gradients to represent geostrophic winds. One time step lagged Hs is also included as a predictor, which could be interpreted as the first order derivative in the spectral energy balance governing equation. Further, based on the frequency/directional dispersion theory of waves, the swell component is accounted for by using a set of selected principal components derived from the squared SLP gradient vectors (including magnitudes and directions). The effect of non-Gaussian (non-negative) variables is also assessed by applying two types of transformation to the data. The proposed method is evaluated and shown to have good skills for the study area (Catalan coast). This method can be used to project possible future wave climate change for use in coastal impact assessment studies. It is used in this study to project the wave climate for the study area that corresponds to 5 sets of regional climate model (RCM) atmospheric projections, which were made by different RCMs forced by the same global circulation model (GCM), or by the same RCM forced by two GCMs. For the season analyzed (winter), the results show that the uncertainty due to using different GCMs to drive the same RCM is greater than that due to using different RCMs driven by the same GCM.

  4. Potential benefit of the CT adaptive statistical iterative reconstruction method for pediatric cardiac diagnosis

    NASA Astrophysics Data System (ADS)

    Miéville, Frédéric A.; Ayestaran, Paul; Argaud, Christophe; Rizzo, Elena; Ou, Phalla; Brunelle, Francis; Gudinchet, François; Bochud, François; Verdun, Francis R.

    2010-04-01

    Adaptive Statistical Iterative Reconstruction (ASIR) is a new imaging reconstruction technique recently introduced by General Electric (GE). This technique, when combined with a conventional filtered back-projection (FBP) approach, is able to improve the image noise reduction. To quantify the benefits provided on the image quality and the dose reduction by the ASIR method with respect to the pure FBP one, the standard deviation (SD), the modulation transfer function (MTF), the noise power spectrum (NPS), the image uniformity and the noise homogeneity were examined. Measurements were performed on a control quality phantom when varying the CT dose index (CTDIvol) and the reconstruction kernels. A 64-MDCT was employed and raw data were reconstructed with different percentages of ASIR on a CT console dedicated for ASIR reconstruction. Three radiologists also assessed a cardiac pediatric exam reconstructed with different ASIR percentages using the visual grading analysis (VGA) method. For the standard, soft and bone reconstruction kernels, the SD is reduced when the ASIR percentage increases up to 100% with a higher benefit for low CTDIvol. MTF medium frequencies were slightly enhanced and modifications of the NPS shape curve were observed. However for the pediatric cardiac CT exam, VGA scores indicate an upper limit of the ASIR benefit. 40% of ASIR was observed as the best trade-off between noise reduction and clinical realism of organ images. Using phantom results, 40% of ASIR corresponded to an estimated dose reduction of 30% under pediatric cardiac protocol conditions. In spite of this discrepancy between phantom and clinical results, the ASIR method is as an important option when considering the reduction of radiation dose, especially for pediatric patients.

  5. Developing Students' Thought Processes for Choosing Appropriate Statistical Methods

    ERIC Educational Resources Information Center

    Murray, James; Knowles, Elizabeth

    2014-01-01

    Students often struggle to select appropriate statistical tests when investigating research questions. The authors present a lesson study designed to make students' thought processes visible while considering this choice. The authors taught their students a way to organize knowledge about statistical tests and observed its impact in the…

  6. Comparing Methods for Item Analysis: The Impact of Different Item-Selection Statistics on Test Difficulty

    ERIC Educational Resources Information Center

    Jones, Andrew T.

    2011-01-01

    Practitioners often depend on item analysis to select items for exam forms and have a variety of options available to them. These include the point-biserial correlation, the agreement statistic, the B index, and the phi coefficient. Although research has demonstrated that these statistics can be useful for item selection, no research as of yet has…

  7. The T(ea) Test: Scripted Stories Increase Statistical Method Selection Skills

    ERIC Educational Resources Information Center

    Hackathorn, Jana; Ashdown, Brien

    2015-01-01

    To teach statistics, teachers must attempt to overcome pedagogical obstacles, such as dread, anxiety, and boredom. There are many options available to teachers that facilitate a pedagogically conducive environment in the classroom. The current study examined the effectiveness of incorporating scripted stories and humor into statistical method…

  8. An Inferential Confidence Interval Method of Establishing Statistical Equivalence that Corrects Tryon's (2001) Reduction Factor

    ERIC Educational Resources Information Center

    Tryon, Warren W.; Lewis, Charles

    2008-01-01

    Evidence of group matching frequently takes the form of a nonsignificant test of statistical difference. Theoretical hypotheses of no difference are also tested in this way. These practices are flawed in that null hypothesis statistical testing provides evidence against the null hypothesis and failing to reject H[subscript 0] is not evidence…

  9. An Expressed Preference Determination of College Students' Valuation of Statistical Lives: Methods and Implications

    ERIC Educational Resources Information Center

    Brady, Kevin L.

    2008-01-01

    Government agencies typically apply a general value of statistical life (VSL) estimate when performing cost-benefit analysis (CBA). However, theory suggests that college students attach a value to statistical lives that differs from society's VSL; therefore, CBA may lead to inefficient levels of risk reduction among students. A contingent…

  10. Beyond Statistical Methods: Teaching Critical Thinking to First-Year University Students

    ERIC Educational Resources Information Center

    David, Irene; Brown, Jennifer Ann

    2012-01-01

    We discuss a major change in the way we teach our first-year statistics course. We have redesigned this course with emphasis on teaching critical thinking. We recognized that most of the students take the course for general knowledge and support of other majors, and very few are planning to major in statistics. We identified the essential aspects…

  11. USING STATISTICAL METHODS FOR WATER QUALITY MANAGEMENT: ISSUES, PROBLEMS AND SOLUTIONS

    EPA Science Inventory

    This book is readable, comprehensible and I anticipate, usable. The author has an enthusiasm which comes out in the text. Statistics is presented as a living breathing subject, still being debated, defined, and refined. This statistics book actually has examples in the field...

  12. Comparison of precipitation nowcasting by extrapolation and statistical-advection methods

    NASA Astrophysics Data System (ADS)

    Sokol, Zbynek; Kitzmiller, David; Pesice, Petr; Mejsnar, Jan

    2013-04-01

    Two models for nowcasting of 1-h, 2-h and 3-h precipitation in the warm part of the year were evaluated. The first model was based on the extrapolation of observed radar reflectivity (COTREC-IPA) and the second one combined the extrapolation with the application of a statistical model (SAMR). The accuracy of the model forecasts was evaluated on independent data using the standard measures of root-mean-squared-error, absolute error, bias and correlation coefficient as well as by spatial verification methods Fractions Skill Score and SAL technique. The results show that SAMR yields slightly better forecasts during the afternoon period. On the other hand very small or no improvement is realized at night and in the very early morning. COTREC-IPA and SAMR forecast a very similar horizontal structure of precipitation patterns but the model forecasts differ in values. SAMR, similarly as COTREC-IPA, is not able to develop new storms or significantly intensify already existing storms. This is caused by a large uncertainty regarding future development. On the other hand, the SAMR model can reliably predict decreases in precipitation intensity.

  13. Integrating Symbolic and Statistical Methods for Testing Intelligent Systems Applications to Machine Learning and Computer Vision

    SciTech Connect

    Jha, Sumit Kumar; Pullum, Laura L; Ramanathan, Arvind

    2016-01-01

    Embedded intelligent systems ranging from tiny im- plantable biomedical devices to large swarms of autonomous un- manned aerial systems are becoming pervasive in our daily lives. While we depend on the flawless functioning of such intelligent systems, and often take their behavioral correctness and safety for granted, it is notoriously difficult to generate test cases that expose subtle errors in the implementations of machine learning algorithms. Hence, the validation of intelligent systems is usually achieved by studying their behavior on representative data sets, using methods such as cross-validation and bootstrapping.In this paper, we present a new testing methodology for studying the correctness of intelligent systems. Our approach uses symbolic decision procedures coupled with statistical hypothesis testing to. We also use our algorithm to analyze the robustness of a human detection algorithm built using the OpenCV open-source computer vision library. We show that the human detection implementation can fail to detect humans in perturbed video frames even when the perturbations are so small that the corresponding frames look identical to the naked eye.

  14. Spiked proteomic standard dataset for testing label-free quantitative software and statistical methods

    PubMed Central

    Ramus, Claire; Hovasse, Agnès; Marcellin, Marlène; Hesse, Anne-Marie; Mouton-Barbosa, Emmanuelle; Bouyssié, David; Vaca, Sebastian; Carapito, Christine; Chaoui, Karima; Bruley, Christophe; Garin, Jérôme; Cianférani, Sarah; Ferro, Myriam; Dorssaeler, Alain Van; Burlet-Schiltz, Odile; Schaeffer, Christine; Couté, Yohann; Gonzalez de Peredo, Anne

    2015-01-01

    This data article describes a controlled, spiked proteomic dataset for which the “ground truth” of variant proteins is known. It is based on the LC-MS analysis of samples composed of a fixed background of yeast lysate and different spiked amounts of the UPS1 mixture of 48 recombinant proteins. It can be used to objectively evaluate bioinformatic pipelines for label-free quantitative analysis, and their ability to detect variant proteins with good sensitivity and low false discovery rate in large-scale proteomic studies. More specifically, it can be useful for tuning software tools parameters, but also testing new algorithms for label-free quantitative analysis, or for evaluation of downstream statistical methods. The raw MS files can be downloaded from ProteomeXchange with identifier PXD001819. Starting from some raw files of this dataset, we also provide here some processed data obtained through various bioinformatics tools (including MaxQuant, Skyline, MFPaQ, IRMa-hEIDI and Scaffold) in different workflows, to exemplify the use of such data in the context of software benchmarking, as discussed in details in the accompanying manuscript [1]. The experimental design used here for data processing takes advantage of the different spike levels introduced in the samples composing the dataset, and processed data are merged in a single file to facilitate the evaluation and illustration of software tools results for the detection of variant proteins with different absolute expression levels and fold change values. PMID:26862574

  15. Statistical methods for efficient design of community surveys of response to noise: Random coefficients regression models

    NASA Technical Reports Server (NTRS)

    Tomberlin, T. J.

    1985-01-01

    Research studies of residents' responses to noise consist of interviews with samples of individuals who are drawn from a number of different compact study areas. The statistical techniques developed provide a basis for those sample design decisions. These techniques are suitable for a wide range of sample survey applications. A sample may consist of a random sample of residents selected from a sample of compact study areas, or in a more complex design, of a sample of residents selected from a sample of larger areas (e.g., cities). The techniques may be applied to estimates of the effects on annoyance of noise level, numbers of noise events, the time-of-day of the events, ambient noise levels, or other factors. Methods are provided for determining, in advance, how accurately these effects can be estimated for different sample sizes and study designs. Using a simple cost function, they also provide for optimum allocation of the sample across the stages of the design for estimating these effects. These techniques are developed via a regression model in which the regression coefficients are assumed to be random, with components of variance associated with the various stages of a multi-stage sample design.

  16. A statistical method to estimate outflow volume in case of levee breach due to overtopping

    NASA Astrophysics Data System (ADS)

    Brandimarte, Luigia; Martina, Mario; Dottori, Francesco; Mazzoleni, Maurizio

    2015-04-01

    The aim of this study is to propose a statistical method to assess the outflowing water volume through a levee breach, due to overtopping, in case of three different types of grass cover quality. The first step in the proposed methodology is the definition of the reliability function, a the relation between loading and resistance conditions on the levee system, in case of overtopping. Secondly, the fragility curve, which relates the probability of failure with loading condition over the levee system, is estimated having defined the stochastic variables in the reliability function. Thus, different fragility curves are assessed in case of different scenarios of grass cover quality. Then, a levee breach model is implemented and combined with a 1D hydrodynamic model in order to assess the outflow hydrograph given the water level in the main channel and stochastic values of the breach width. Finally, the water volume is estimated as a combination of the probability density function of the breach width and levee failure. The case study is located in the in 98km-braided reach of Po River, Italy, between the cross-sections of Cremona and Borgoforte. The analysis showed how different counter measures, different grass cover quality in this case, can reduce the probability of failure of the levee system. In particular, for a given values of breach width good levee cover qualities can significantly reduce the outflowing water volume, compared to bad cover qualities, inducing a consequent lower flood risk within the flood-prone area.

  17. Analysis of spatial and temporal water pollution patterns in Lake Dianchi using multivariate statistical methods.

    PubMed

    Yang, Yong-Hui; Zhou, Feng; Guo, Huai-Cheng; Sheng, Hu; Liu, Hui; Dao, Xu; He, Cheng-Jie

    2010-11-01

    Various multivariate statistical methods including cluster analysis (CA), discriminant analysis (DA), factor analysis (FA), and principal component analysis (PCA) were used to explain the spatial and temporal patterns of surface water pollution in Lake Dianchi. The dataset, obtained during the period 2003-2007 from the Kunming Environmental Monitoring Center, consisted of 12 variables surveyed monthly at eight sites. The CA grouped the 12 months into two groups, August-September and the remainder, and divided the lake into two regions based on their different physicochemical properties and pollution levels. The DA showed the best results for data reduction and pattern recognition in both temporal and spatial analysis. It calculated four parameters (TEMP, pH, CODMn, and Chl-a) to 85.4% correct assignment in the temporal analysis and three parameters (BOD, NH₄+-N, and TN) to almost 71.7% correct assignment in spatial analysis of the two clusters. The FA/PCA applied to datasets of two special clusters of the lake calculated four factors for each region, capturing 72.5% and 62.5% of the total variance, respectively. Strong loadings included DO, BOD, TN, CODCr, CODMn, NH₄+-N, TP, and EC. In addition, box-whisker plots and GIS further facilitated and supported the multivariate analysis results. PMID:19936953

  18. An Efficient Augmented Lagrangian Method for Statistical X-Ray CT Image Reconstruction

    PubMed Central

    Li, Jiaojiao; Niu, Shanzhou; Huang, Jing; Bian, Zhaoying; Feng, Qianjin; Yu, Gaohang; Liang, Zhengrong; Chen, Wufan; Ma, Jianhua

    2015-01-01

    Statistical iterative reconstruction (SIR) for X-ray computed tomography (CT) under the penalized weighted least-squares criteria can yield significant gains over conventional analytical reconstruction from the noisy measurement. However, due to the nonlinear expression of the objective function, most exiting algorithms related to the SIR unavoidably suffer from heavy computation load and slow convergence rate, especially when an edge-preserving or sparsity-based penalty or regularization is incorporated. In this work, to address abovementioned issues of the general algorithms related to the SIR, we propose an adaptive nonmonotone alternating direction algorithm in the framework of augmented Lagrangian multiplier method, which is termed as “ALM-ANAD”. The algorithm effectively combines an alternating direction technique with an adaptive nonmonotone line search to minimize the augmented Lagrangian function at each iteration. To evaluate the present ALM-ANAD algorithm, both qualitative and quantitative studies were conducted by using digital and physical phantoms. Experimental results show that the present ALM-ANAD algorithm can achieve noticeable gains over the classical nonlinear conjugate gradient algorithm and state-of-the-art split Bregman algorithm in terms of noise reduction, contrast-to-noise ratio, convergence rate, and universal quality index metrics. PMID:26495975

  19. Statistical methods for biodosimetry in the presence of both Berkson and classical measurement error

    NASA Astrophysics Data System (ADS)

    Miller, Austin

    In radiation epidemiology, the true dose received by those exposed cannot be assessed directly. Physical dosimetry uses a deterministic function of the source term, distance and shielding to estimate dose. For the atomic bomb survivors, the physical dosimetry system is well established. The classical measurement errors plaguing the location and shielding inputs to the physical dosimetry system are well known. Adjusting for the associated biases requires an estimate for the classical measurement error variance, for which no data-driven estimate exists. In this case, an instrumental variable solution is the most viable option to overcome the classical measurement error indeterminacy. Biological indicators of dose may serve as instrumental variables. Specification of the biodosimeter dose-response model requires identification of the radiosensitivity variables, for which we develop statistical definitions and variables. More recently, researchers have recognized Berkson error in the dose estimates, introduced by averaging assumptions for many components in the physical dosimetry system. We show that Berkson error induces a bias in the instrumental variable estimate of the dose-response coefficient, and then address the estimation problem. This model is specified by developing an instrumental variable mixed measurement error likelihood function, which is then maximized using a Monte Carlo EM Algorithm. These methods produce dose estimates that incorporate information from both physical and biological indicators of dose, as well as the first instrumental variable based data-driven estimate for the classical measurement error variance.

  20. Foundations of statistical methods for multiple sequence alignment and structure prediction

    SciTech Connect

    Lawrence, C.

    1995-12-31

    Statistical algorithms have proven to be useful in computational molecular biology. Many statistical problems are most easily addressed by pretending that critical missing data are available. For some problems statistical inference in facilitated by creating a set of latent variables, none of whose variables are observed. A key observation is that conditional probabilities for the values of the missing data can be inferred by application of Bayes theorem to the observed data. The statistical framework described in this paper employs Boltzmann like models, permutated data likelihood, EM, and Gibbs sampler algorithms. This tutorial reviews the common statistical framework behind all of these algorithms largely in tabular or graphical terms, illustrates its application, and describes the biological underpinnings of the models used.

  1. Examination of two methods for statistical analysis of data with magnitude and direction emphasizing vestibular research applications

    NASA Technical Reports Server (NTRS)

    Calkins, D. S.

    1998-01-01

    When the dependent (or response) variable response variable in an experiment has direction and magnitude, one approach that has been used for statistical analysis involves splitting magnitude and direction and applying univariate statistical techniques to the components. However, such treatment of quantities with direction and magnitude is not justifiable mathematically and can lead to incorrect conclusions about relationships among variables and, as a result, to flawed interpretations. This note discusses a problem with that practice and recommends mathematically correct procedures to be used with dependent variables that have direction and magnitude for 1) computation of mean values, 2) statistical contrasts of and confidence intervals for means, and 3) correlation methods.

  2. Meta-analysis as Statistical and Analytical Method of Journal’s Content Scientific Evaluation

    PubMed Central

    Masic, Izet; Begic, Edin

    2015-01-01

    Introduction: A meta-analysis is a statistical and analytical method which combines and synthesizes different independent studies and integrates their results into one common result. Goal: Analysis of the journals “Medical Archives”, “Materia Socio Medica” and “Acta Informatica Medica”, which are located in the most eminent indexed databases of the biomedical milieu. Material and methods: The study has retrospective and descriptive character, and included the period of the calendar year 2014. Study included six editions of all three journals (total of 18 journals). Results: In this period was published a total of 291 articles (in the “Medical Archives” 110, “Materia Socio Medica” 97, and in “Acta Informatica Medica” 84). The largest number of articles was original articles. Small numbers have been published as professional, review articles and case reports. Clinical events were most common in the first two journals, while in the journal “Acta Informatica Medica” belonged to the field of medical informatics, as part of pre-clinical medical disciplines. Articles are usually required period of fifty to fifty nine days for review. Articles were received from four continents, mostly from Europe. The authors are most often from the territory of Bosnia and Herzegovina, then Iran, Kosovo and Macedonia. Conclusion: The number of articles published each year is increasing, with greater participation of authors from different continents and abroad. Clinical medical disciplines are the most common, with the broader spectrum of topics and with a growing number of original articles. Greater support of the wider scientific community is needed for further development of all three of the aforementioned journals. PMID:25870484

  3. "Geo-statistics methods and neural networks in geophysical applications: A case study"

    NASA Astrophysics Data System (ADS)

    Rodriguez Sandoval, R.; Urrutia Fucugauchi, J.; Ramirez Cruz, L. C.

    2008-12-01

    The study is focus in the Ebano-Panuco basin of northeastern Mexico, which is being explored for hydrocarbon reservoirs. These reservoirs are in limestones and there is interest in determining porosity and permeability in the carbonate sequences. The porosity maps presented in this study are estimated from application of multiattribute and neural networks techniques, which combine geophysics logs and 3-D seismic data by means of statistical relationships. The multiattribute analysis is a process to predict a volume of any underground petrophysical measurement from well-log and seismic data. The data consist of a series of target logs from wells which tie a 3-D seismic volume. The target logs are neutron porosity logs. From the 3-D seismic volume a series of sample attributes is calculated. The objective of this study is to derive a set of attributes and the target log values. The selected set is determined by a process of forward stepwise regression. The analysis can be linear or nonlinear. In the linear mode the method consists of a series of weights derived by least-square minimization. In the nonlinear mode, a neural network is trained using the select attributes as inputs. In this case we used a probabilistic neural network PNN. The method is applied to a real data set from PEMEX. For better reservoir characterization the porosity distribution was estimated using both techniques. The case shown a continues improvement in the prediction of the porosity from the multiattribute to the neural network analysis. The improvement is in the training and the validation, which are important indicators of the reliability of the results. The neural network showed an improvement in resolution over the multiattribute analysis. The final maps provide more realistic results of the porosity distribution.

  4. Adequate histologic sectioning of prostate needle biopsies.

    PubMed

    Bostwick, David G; Kahane, Hillel

    2013-08-01

    No standard method exists for sampling prostate needle biopsies, although most reports claim to embed 3 cores per block and obtain 3 slices from each block. This study was undertaken to determine the extent of histologic sectioning necessary for optimal examination of prostate biopsies. We prospectively compared the impact on cancer yield of submitting 1 biopsy core per cassette (biopsies from January 2010) with 3 cores per cassette (biopsies from August 2010) from a large national reference laboratory. Between 6 and 12 slices were obtained with the former 1-core method, resulting in 3 to 6 slices being placed on each of 2 slides; for the latter 3-core method, a limit of 6 slices was obtained, resulting in 3 slices being place on each of 2 slides. A total of 6708 sets of 12 to 18 core biopsies were studied, including 3509 biopsy sets from the 1-biopsy-core-per-cassette group (January 2010) and 3199 biopsy sets from the 3-biopsy-cores-percassette group (August 2010). The yield of diagnoses was classified as benign, atypical small acinar proliferation, high-grade prostatic intraepithelial neoplasia, and cancer and was similar with the 2 methods: 46.2%, 8.2%, 4.5%, and 41.1% and 46.7%, 6.3%, 4.4%, and 42.6%, respectively (P = .02). Submission of 1 core or 3 cores per cassette had no effect on the yield of atypical small acinar proliferation, prostatic intraepithelial neoplasia, or cancer in prostate needle biopsies. Consequently, we recommend submission of 3 cores per cassette to minimize labor and cost of processing. PMID:23764163

  5. Statistical Diversions

    ERIC Educational Resources Information Center

    Petocz, Peter; Sowey, Eric

    2008-01-01

    In this article, the authors focus on hypothesis testing--that peculiarly statistical way of deciding things. Statistical methods for testing hypotheses were developed in the 1920s and 1930s by some of the most famous statisticians, in particular Ronald Fisher, Jerzy Neyman and Egon Pearson, who laid the foundations of almost all modern methods of…

  6. Statistical prediction of dynamic distortion of inlet flow using minimum dynamic measurement. An application to the Melick statistical method and inlet flow dynamic distortion prediction without RMS measurements

    NASA Technical Reports Server (NTRS)

    Schweikhard, W. G.; Chen, Y. S.

    1986-01-01

    The Melick method of inlet flow dynamic distortion prediction by statistical means is outlined. A hypothetic vortex model is used as the basis for the mathematical formulations. The main variables are identified by matching the theoretical total pressure rms ratio with the measured total pressure rms ratio. Data comparisons, using the HiMAT inlet test data set, indicate satisfactory prediction of the dynamic peak distortion for cases with boundary layer control device vortex generators. A method for the dynamic probe selection was developed. Validity of the probe selection criteria is demonstrated by comparing the reduced-probe predictions with the 40-probe predictions. It is indicated that the the number of dynamic probes can be reduced to as few as two and still retain good accuracy.

  7. Multivariate statistical data analysis methods for detecting baroclinic wave interactions in the thermally driven rotating annulus

    NASA Astrophysics Data System (ADS)

    von Larcher, Thomas; Harlander, Uwe; Alexandrov, Kiril; Wang, Yongtai

    2010-05-01

    Experiments on baroclinic wave instabilities in a rotating cylindrical gap have been long performed, e.g., to unhide regular waves of different zonal wave number, to better understand the transition to the quasi-chaotic regime, and to reveal the underlying dynamical processes of complex wave flows. We present the application of appropriate multivariate data analysis methods on time series data sets acquired by the use of non-intrusive measurement techniques of a quite different nature. While the high accurate Laser-Doppler-Velocimetry (LDV ) is used for measurements of the radial velocity component at equidistant azimuthal positions, a high sensitive thermographic camera measures the surface temperature field. The measurements are performed at particular parameter points, where our former studies show that kinds of complex wave patterns occur [1, 2]. Obviously, the temperature data set has much more information content as the velocity data set due to the particular measurement techniques. Both sets of time series data are analyzed by using multivariate statistical techniques. While the LDV data sets are studied by applying the Multi-Channel Singular Spectrum Analysis (M - SSA), the temperature data sets are analyzed by applying the Empirical Orthogonal Functions (EOF ). Our goal is (a) to verify the results yielded with the analysis of the velocity data and (b) to compare the data analysis methods. Therefor, the temperature data are processed in a way to become comparable to the LDV data, i.e. reducing the size of the data set in such a manner that the temperature measurements would imaginary be performed at equidistant azimuthal positions only. This approach initially results in a great loss of information. But applying the M - SSA to the reduced temperature data sets enable us to compare the methods. [1] Th. von Larcher and C. Egbers, Experiments on transitions of baroclinic waves in a differentially heated rotating annulus, Nonlinear Processes in Geophysics

  8. FITTING STATISTICAL DISTRIBUTIONS TO AIR QUALITY DATA BY THE MAXIMUM LIKELIHOOD METHOD

    EPA Science Inventory

    A computer program has been developed for fitting statistical distributions to air pollution data using maximum likelihood estimation. Appropriate uses of this software are discussed and a grouped data example is presented. The program fits the following continuous distributions:...

  9. Zu Problemen statistischer Methoden in der Sprachwissenschaft (Problems of Statistical Methods in Linguistics)

    ERIC Educational Resources Information Center

    Zorn, Klaus

    1973-01-01

    Discussion of statistical apparatus employed in L. Doncheva-Mareva's article on the wide-spread usage of the present and future tense forms with future meaning in German letters, Deutsch als Fremdsprache, n1 1971. (RS)

  10. Low dose dynamic CT myocardial perfusion imaging using a statistical iterative reconstruction method

    SciTech Connect

    Tao, Yinghua; Chen, Guang-Hong; Hacker, Timothy A.; Raval, Amish N.; Van Lysel, Michael S.; Speidel, Michael A.

    2014-07-15

    Purpose: Dynamic CT myocardial perfusion imaging has the potential to provide both functional and anatomical information regarding coronary artery stenosis. However, radiation dose can be potentially high due to repeated scanning of the same region. The purpose of this study is to investigate the use of statistical iterative reconstruction to improve parametric maps of myocardial perfusion derived from a low tube current dynamic CT acquisition. Methods: Four pigs underwent high (500 mA) and low (25 mA) dose dynamic CT myocardial perfusion scans with and without coronary occlusion. To delineate the affected myocardial territory, an N-13 ammonia PET perfusion scan was performed for each animal in each occlusion state. Filtered backprojection (FBP) reconstruction was first applied to all CT data sets. Then, a statistical iterative reconstruction (SIR) method was applied to data sets acquired at low dose. Image voxel noise was matched between the low dose SIR and high dose FBP reconstructions. CT perfusion maps were compared among the low dose FBP, low dose SIR and high dose FBP reconstructions. Numerical simulations of a dynamic CT scan at high and low dose (20:1 ratio) were performed to quantitatively evaluate SIR and FBP performance in terms of flow map accuracy, precision, dose efficiency, and spatial resolution. Results: Forin vivo studies, the 500 mA FBP maps gave −88.4%, −96.0%, −76.7%, and −65.8% flow change in the occluded anterior region compared to the open-coronary scans (four animals). The percent changes in the 25 mA SIR maps were in good agreement, measuring −94.7%, −81.6%, −84.0%, and −72.2%. The 25 mA FBP maps gave unreliable flow measurements due to streaks caused by photon starvation (percent changes of +137.4%, +71.0%, −11.8%, and −3.5%). Agreement between 25 mA SIR and 500 mA FBP global flow was −9.7%, 8.8%, −3.1%, and 26.4%. The average variability of flow measurements in a nonoccluded region was 16.3%, 24.1%, and 937

  11. Low dose dynamic CT myocardial perfusion imaging using a statistical iterative reconstruction method

    PubMed Central

    Tao, Yinghua; Chen, Guang-Hong; Hacker, Timothy A.; Raval, Amish N.; Van Lysel, Michael S.; Speidel, Michael A.

    2014-01-01

    Purpose: Dynamic CT myocardial perfusion imaging has the potential to provide both functional and anatomical information regarding coronary artery stenosis. However, radiation dose can be potentially high due to repeated scanning of the same region. The purpose of this study is to investigate the use of statistical iterative reconstruction to improve parametric maps of myocardial perfusion derived from a low tube current dynamic CT acquisition. Methods: Four pigs underwent high (500 mA) and low (25 mA) dose dynamic CT myocardial perfusion scans with and without coronary occlusion. To delineate the affected myocardial territory, an N-13 ammonia PET perfusion scan was performed for each animal in each occlusion state. Filtered backprojection (FBP) reconstruction was first applied to all CT data sets. Then, a statistical iterative reconstruction (SIR) method was applied to data sets acquired at low dose. Image voxel noise was matched between the low dose SIR and high dose FBP reconstructions. CT perfusion maps were compared among the low dose FBP, low dose SIR and high dose FBP reconstructions. Numerical simulations of a dynamic CT scan at high and low dose (20:1 ratio) were performed to quantitatively evaluate SIR and FBP performance in terms of flow map accuracy, precision, dose efficiency, and spatial resolution. Results: Forin vivo studies, the 500 mA FBP maps gave −88.4%, −96.0%, −76.7%, and −65.8% flow change in the occluded anterior region compared to the open-coronary scans (four animals). The percent changes in the 25 mA SIR maps were in good agreement, measuring −94.7%, −81.6%, −84.0%, and −72.2%. The 25 mA FBP maps gave unreliable flow measurements due to streaks caused by photon starvation (percent changes of +137.4%, +71.0%, −11.8%, and −3.5%). Agreement between 25 mA SIR and 500 mA FBP global flow was −9.7%, 8.8%, −3.1%, and 26.4%. The average variability of flow measurements in a nonoccluded region was 16.3%, 24.1%, and 937

  12. Epoch of reionization window. II. Statistical methods for foreground wedge reduction

    NASA Astrophysics Data System (ADS)

    Liu, Adrian; Parsons, Aaron R.; Trott, Cathryn M.

    2014-07-01

    For there to be a successful measurement of the 21 cm epoch of reionization (EoR) power spectrum, it is crucial that strong foreground contaminants be robustly suppressed. These foregrounds come from a variety of sources (such as Galactic synchrotron emission and extragalactic point sources), but almost all share the property of being spectrally smooth and, when viewed through the chromatic response of an interferometer, occupy a signature "wedge" region in cylindrical k⊥k∥ Fourier space. The complement of the foreground wedge is termed the "EoR window" and is expected to be mostly foreground-free, allowing clean measurements of the power spectrum. This paper is a sequel to a previous paper that established a rigorous mathematical framework for describing the foreground wedge and the EoR window. Here, we use our framework to explore statistical methods by which the EoR window can be enlarged, thereby increasing the sensitivity of a power spectrum measurement. We adapt the Feldman-Kaiser-Peacock approximation (commonly used in galaxy surveys) for 21 cm cosmology and also compare the optimal quadratic estimator to simpler estimators that ignore covariances between different Fourier modes. The optimal quadratic estimator is found to suppress foregrounds by an extra factor of ˜105 in power at the peripheries of the EoR window, boosting the detection of the cosmological signal from 12σ to 50σ at the midpoint of reionization in our fiducial models. If numerical issues can be finessed, decorrelation techniques allow the EoR window to be further enlarged, enabling measurements to be made deep within the foreground wedge. These techniques do not assume that foreground is Gaussian distributed, and we additionally prove that a final round of foreground subtraction can be performed after decorrelation in a way that is guaranteed to have no cosmological signal loss.

  13. Adipose Tissue - Adequate, Accessible Regenerative Material.

    PubMed

    Kolaparthy, Lakshmi Kanth; Sanivarapu, Sahitya; Moogla, Srinivas; Kutcham, Rupa Sruthi

    2015-11-01

    The potential use of stem cell based therapies for the repair and regeneration of various tissues offers a paradigm shift that may provide alternative therapeutic solutions for a number of diseases. The use of either embryonic stem cells (ESCs) or induced pluripotent stem cells in clinical situations is limited due to cell regulations and to technical and ethical considerations involved in genetic manipulation of human ESCs, even though these cells are highly beneficial. Mesenchymal stem cells seen to be an ideal population of stem cells in particular, Adipose derived stem cells (ASCs) which can be obtained in large number and easily harvested from adipose tissue. It is ubiquitously available and has several advantages compared to other sources as easily accessible in large quantities with minimal invasive harvesting procedure, and isolation of adipose derived mesenchymal stem cells yield a high amount of stem cells which is essential for stem cell based therapies and tissue engineering. Recently, periodontal tissue regeneration using ASCs has been examined in some animal models. This method has potential in the regeneration of functional periodontal tissues because various secreted growth factors from ASCs might not only promote the regeneration of periodontal tissues but also encourage neovascularization of the damaged tissues. This review summarizes the sources, isolation and characteristics of adipose derived stem cells and its potential role in periodontal regeneration is discussed. PMID:26634060

  14. Adipose Tissue - Adequate, Accessible Regenerative Material

    PubMed Central

    Kolaparthy, Lakshmi Kanth.; Sanivarapu, Sahitya; Moogla, Srinivas; Kutcham, Rupa Sruthi

    2015-01-01

    The potential use of stem cell based therapies for the repair and regeneration of various tissues offers a paradigm shift that may provide alternative therapeutic solutions for a number of diseases. The use of either embryonic stem cells (ESCs) or induced pluripotent stem cells in clinical situations is limited due to cell regulations and to technical and ethical considerations involved in genetic manipulation of human ESCs, even though these cells are highly beneficial. Mesenchymal stem cells seen to be an ideal population of stem cells in particular, Adipose derived stem cells (ASCs) which can be obtained in large number and easily harvested from adipose tissue. It is ubiquitously available and has several advantages compared to other sources as easily accessible in large quantities with minimal invasive harvesting procedure, and isolation of adipose derived mesenchymal stem cells yield a high amount of stem cells which is essential for stem cell based therapies and tissue engineering. Recently, periodontal tissue regeneration using ASCs has been examined in some animal models. This method has potential in the regeneration of functional periodontal tissues because various secreted growth factors from ASCs might not only promote the regeneration of periodontal tissues but also encourage neovascularization of the damaged tissues. This review summarizes the sources, isolation and characteristics of adipose derived stem cells and its potential role in periodontal regeneration is discussed. PMID:26634060

  15. 21 CFR 201.5 - Drugs; adequate directions for use.

    Code of Federal Regulations, 2010 CFR

    2010-04-01

    ... 21 Food and Drugs 4 2010-04-01 2010-04-01 false Drugs; adequate directions for use. 201.5 Section...) DRUGS: GENERAL LABELING General Labeling Provisions § 201.5 Drugs; adequate directions for use. Adequate directions for use means directions under which the layman can use a drug safely and for the purposes...

  16. 21 CFR 201.5 - Drugs; adequate directions for use.

    Code of Federal Regulations, 2011 CFR

    2011-04-01

    ... 21 Food and Drugs 4 2011-04-01 2011-04-01 false Drugs; adequate directions for use. 201.5 Section...) DRUGS: GENERAL LABELING General Labeling Provisions § 201.5 Drugs; adequate directions for use. Adequate directions for use means directions under which the layman can use a drug safely and for the purposes...

  17. 4 CFR 200.14 - Responsibility for maintaining adequate safeguards.

    Code of Federal Regulations, 2010 CFR

    2010-01-01

    ... 4 Accounts 1 2010-01-01 2010-01-01 false Responsibility for maintaining adequate safeguards. 200.14 Section 200.14 Accounts RECOVERY ACCOUNTABILITY AND TRANSPARENCY BOARD PRIVACY ACT OF 1974 § 200.14 Responsibility for maintaining adequate safeguards. The Board has the responsibility for maintaining adequate technical, physical, and...

  18. 10 CFR 1304.114 - Responsibility for maintaining adequate safeguards.

    Code of Federal Regulations, 2010 CFR

    2010-01-01

    ... 10 Energy 4 2010-01-01 2010-01-01 false Responsibility for maintaining adequate safeguards. 1304.114 Section 1304.114 Energy NUCLEAR WASTE TECHNICAL REVIEW BOARD PRIVACY ACT OF 1974 § 1304.114 Responsibility for maintaining adequate safeguards. The Board has the responsibility for maintaining adequate technical, physical, and security...

  19. 10 CFR 1304.114 - Responsibility for maintaining adequate safeguards.

    Code of Federal Regulations, 2012 CFR

    2012-01-01

    ... 10 Energy 4 2012-01-01 2012-01-01 false Responsibility for maintaining adequate safeguards. 1304.114 Section 1304.114 Energy NUCLEAR WASTE TECHNICAL REVIEW BOARD PRIVACY ACT OF 1974 § 1304.114 Responsibility for maintaining adequate safeguards. The Board has the responsibility for maintaining adequate technical, physical, and security...

  20. 4 CFR 200.14 - Responsibility for maintaining adequate safeguards.

    Code of Federal Regulations, 2011 CFR

    2011-01-01

    ... 4 Accounts 1 2011-01-01 2011-01-01 false Responsibility for maintaining adequate safeguards. 200....14 Responsibility for maintaining adequate safeguards. The Board has the responsibility for maintaining adequate technical, physical, and security safeguards to prevent unauthorized disclosure...

  1. 21 CFR 314.126 - Adequate and well-controlled studies.

    Code of Federal Regulations, 2011 CFR

    2011-04-01

    ...-evident (general anesthetics, drug metabolism). (3) The method of selection of subjects provides adequate... respect to pertinent variables such as age, sex, severity of disease, duration of disease, and use of... 21 Food and Drugs 5 2011-04-01 2011-04-01 false Adequate and well-controlled studies....

  2. Evaluation of aerosol sources at European high altitude background sites with trajectory statistical methods

    NASA Astrophysics Data System (ADS)

    Salvador, P.; Artíñano, B.; Pio, C. A.; Afonso, J.; Puxbaum, H.; Legrand, M.; Hammer, S.; Kaiser, A.

    2009-04-01

    During the last years, the analysis of a great number of back-trajectories from receptor sites has turned out to be a valuable tool to identify sources and sinks areas of atmospheric particulate matter (PM) or to reconstruct their average spatial distribution. A number of works have applied different trajectory statistical methods (TSM), which allow working simultaneously with back-trajectories computed from one or several receptor points and PM concentration values registered there. In spite of these methods have many limitations, they are simple and effective methods to detect the relevant source regions and the air flow regimes which are connected with regional and large-scale air pollution transport. In this study 5-day backward air trajectories arriving over 3 monitoring sites, were utilised and analysed simultaneously with the PM levels and chemical composition values registered there. These sites are located in the centre of Europe and can be classified into natural continental background (Schauinsland-SIL in Germany (1205 m asl), Puy de Dôme-PDD in France (1450 m asl) and Sonnblick-SBO in Austria (3106 m asl)). In the framework of the CARBOSOL European project, weekly aerosol samples were collected with High Volume Samplers (DIGITEL DH77) and PM10 (SIL and PDD) or PM2.5 (SBO) inlets, on quartz fibre filters. Filter samples were treated and analyzed for determining the levels of major organic fractions (OC, EC) and inorganic ions. Additionally, analyses for specific organic compounds were also carried out whenever was possible (Pio et al., 2007). For each day of the sampling period, four trajectories ending at 00:00, 06:00, 12:00 and 18:00 h UTC have been computed by the Norwegian Institute for Air Research NILU (SIL and PDD) and the Central Institute for Meteorology and Geophysics of Austria (SBO) using the FLEXTRA model (Stohl et al., 1995). In all, more than 8000 complete trajectories were available for analysis, each with 40 endpoints. Firstly air mass

  3. Purchasing a cycle helmet: are retailers providing adequate advice?

    PubMed Central

    Plumridge, E.; McCool, J.; Chetwynd, J.; Langley, J. D.

    1996-01-01

    OBJECTIVES: The aim of this study was to examine the selling of cycle helmets in retail stores with particular reference to the adequacy of advice offered about the fit and securing of helmets. METHODS: All 55 retail outlets selling cycle helmets in Christchurch, New Zealand were studied by participant observation. A research entered each store as a prospective customer and requested assistance to purchase a helmet. She took detailed field notes of the ensuing encounter and these were subsequently transcribed, coded, and analysed. RESULTS: Adequate advice for helmet purchase was given in less than half of the stores. In general the sales assistants in specialist cycle shops were better informed and gave more adequate advice than those in department stores. Those who have good advice also tended to be more good advice also tended to be more active in helping with fitting the helmet. Knowledge about safety standards was apparent in one third of sales assistants. Few stores displayed information for customers about the correct fit of cycle helmets. CONCLUSIONS: These findings suggest that the advice and assistance being given to ensure that cycle helmets fit properly is often inadequate and thus the helmets may fail to fulfil their purpose in preventing injury. Consultation between retailers and policy makers is a necessary first step to improving this situation. PMID:9346053

  4. Identifying relatively high-risk group of coronary artery calcification based on progression rate: statistical and machine learning methods.

    PubMed

    Kim, Ha-Young; Yoo, Sanghyun; Lee, Jihyun; Kam, Hye Jin; Woo, Kyoung-Gu; Choi, Yoon-Ho; Sung, Jidong; Kang, Mira

    2012-01-01

    Coronary artery calcification (CAC) score is an important predictor of coronary artery disease (CAD), which is the primary cause of death in advanced countries. Early prediction of high-risk of CAC based on progression rate enables people to prevent CAD from developing into severe symptoms and diseases. In this study, we developed various classifiers to identify patients in high risk of CAC using statistical and machine learning methods, and compared them with performance accuracy. For statistical approaches, linear regression based classifier and logistic regression model were developed. For machine learning approaches, we suggested three kinds of ensemble-based classifiers (best, top-k, and voting method) to deal with imbalanced distribution of our data set. Ensemble voting method outperformed all other methods including regression methods as AUC was 0.781. PMID:23366360

  5. Application of statistical methods for analyzing the relationship between casting distortion, mold filling, and interfacial heat transfer in sand molds

    SciTech Connect

    Y. A. Owusu

    1999-03-31

    This report presents a statistical method of evaluating geometric tolerances of casting products using point cloud data generated by coordinate measuring machine (CMM) process. The focus of this report is to present a statistical-based approach to evaluate the differences in dimensional and form variations or tolerances of casting products as affected by casting gating system, molding material, casting thickness, and casting orientation at the mold-metal interface. Form parameters such as flatness, parallelism, and other geometric profiles such as angularity, casting length, and height of casting products were obtained and analyzed from CMM point cloud data. In order to relate the dimensional and form errors to the factors under consideration such as flatness and parallelism, a factorial analysis of variance and statistical test means methods were performed to identify the factors that contributed to the casting distortion at the mold-metal interface.

  6. Development of a statistical sampling method for uncertainty analysis with SCALE

    SciTech Connect

    Williams, M.; Wiarda, D.; Smith, H.; Jessee, M. A.; Rearden, B. T.; Zwermann, W.; Klein, M.; Pautz, A.; Krzykacz-Hausmann, B.; Gallner, L.

    2012-07-01

    A new statistical sampling sequence called Sampler has been developed for the SCALE code system. Random values for the input multigroup cross sections are determined by using the XSUSA program to sample uncertainty data provided in the SCALE covariance library. Using these samples, Sampler computes perturbed self-shielded cross sections and propagates the perturbed nuclear data through any specified SCALE analysis sequence, including those for criticality safety, lattice physics with depletion, and shielding calculations. Statistical analysis of the output distributions provides uncertainties and correlations in the desired responses. (authors)

  7. Statistical analysis of dose heterogeneity in circulating blood: Implications for sequential methods of total body irradiation

    SciTech Connect

    Molloy, Janelle A.

    2010-11-15

    Purpose: Improvements in delivery techniques for total body irradiation (TBI) using Tomotherapy and intensity modulated radiation therapy have been proven feasible. Despite the promise of improved dose conformality, the application of these ''sequential'' techniques has been hampered by concerns over dose heterogeneity to circulating blood. The present study was conducted to provide quantitative evidence regarding the potential clinical impact of this heterogeneity. Methods: Blood perfusion was modeled analytically as possessing linear, sinusoidal motion in the craniocaudal dimension. The average perfusion period for human circulation was estimated to be approximately 78 s. Sequential treatment delivery was modeled as a Gaussian-shaped dose cloud with a 10 cm length that traversed a 183 cm patient length at a uniform speed. Total dose to circulating blood voxels was calculated via numerical integration and normalized to 2 Gy per fraction. Dose statistics and equivalent uniform dose (EUD) were calculated for relevant treatment times, radiobiological parameters, blood perfusion rates, and fractionation schemes. The model was then refined to account for random dispersion superimposed onto the underlying periodic blood flow. Finally, a fully stochastic model was developed using binomial and trinomial probability distributions. These models allowed for the analysis of nonlinear sequential treatment modalities and treatment designs that incorporate deliberate organ sparing. Results: The dose received by individual blood voxels exhibited asymmetric behavior that depended on the coherence among the blood velocity, circulation phase, and the spatiotemporal characteristics of the irradiation beam. Heterogeneity increased with the perfusion period and decreased with the treatment time. Notwithstanding, heterogeneity was less than {+-}10% for perfusion periods less than 150 s. The EUD was compromised for radiosensitive cells, long perfusion periods, and short treatment times

  8. From association to prediction: statistical methods for the dissection and selection of complex traits in plants

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Quantification of genotype-to-phenotype associations is central to many scientific investigations, yet the ability to obtain consistent results may be thwarted without appropriate statistical analyses. Models for association can consider confounding effects in the materials and complex genetic inter...

  9. Study of UV Cu + Ne – CuBr laser lifetime by statistical methods

    SciTech Connect

    Iliev, I P; Gocheva-Ilieva, S G

    2013-11-30

    On the basis of a large amount of experimental data, statistical investigation of the average lifetime of a UV Cu + Ne – CuBr laser depending on ten input physical laser parameters is carried out. It is found that only three of the parameters have a substantial influence on the laser lifetime. Physical analysis and interpretation of the results are provided. (lasers)

  10. Is Journal Writing an Effective Method of Reducing Anxiety Towards Statistics?

    ERIC Educational Resources Information Center

    Sgoutas-Emch, Sandra A.; Johnson, Camille Joy

    1998-01-01

    Journal writing was utilized by a group of undergraduate students in their statistics course. Performance, attitudes, and anxiety toward the course were compared with a control group. Results showed that students who kept a journal showed improvement in their grades, lower anxiety before exams, and lower physiological reactions. (JAK)

  11. The Flipped Class: A Method to Address the Challenges of an Undergraduate Statistics Course

    ERIC Educational Resources Information Center

    Wilson, Stephanie Gray

    2013-01-01

    Undergraduate statistics courses are perceived as challenging by both students and instructors. Students' attitudes, motivation, math anxiety, and preparedness can negatively impact the student and instructor experience and have the potential to negatively impact student learning. This article describes an attempt to address some of these…

  12. Stats on the Cheap: Using Free and Inexpensive Internet Resources to Enhance the Teaching of Statistics and Research Methods

    ERIC Educational Resources Information Center

    Hartnett, Jessica L.

    2013-01-01

    The present article describes four free or inexpensive Internet-based activities that can be used to supplement statistics/research methods/general psychology classes. Each activity and subsequent homework assessment is described, as well as homework performance outcome and student opinion data for each activity. (Contains 1 table.)

  13. The Role of Statistics and Research Methods in the Academic Success of Psychology Majors: Do Performance and Enrollment Timing Matter?

    ERIC Educational Resources Information Center

    Freng, Scott; Webber, David; Blatter, Jamin; Wing, Ashley; Scott, Walter D.

    2011-01-01

    Comprehension of statistics and research methods is crucial to understanding psychology as a science (APA, 2007). However, psychology majors sometimes approach methodology courses with derision or anxiety (Onwuegbuzie & Wilson, 2003; Rajecki, Appleby, Williams, Johnson, & Jeschke, 2005); consequently, students may postpone enrollment…

  14. On the statistical significance of excess events: Remarks of caution and the need for a standard method of calculation

    NASA Technical Reports Server (NTRS)

    Staubert, R.

    1985-01-01

    Methods for calculating the statistical significance of excess events and the interpretation of the formally derived values are discussed. It is argued that a simple formula for a conservative estimate should generally be used in order to provide a common understanding of quoted values.

  15. A Meta-Analytic Review of Studies of the Effectiveness of Small-Group Learning Methods on Statistics Achievement

    ERIC Educational Resources Information Center

    Kalaian, Sema A.; Kasim, Rafa M.

    2014-01-01

    This meta-analytic study focused on the quantitative integration and synthesis of the accumulated pedagogical research in undergraduate statistics education literature. These accumulated research studies compared the academic achievement of students who had been instructed using one of the various forms of small-group learning methods to those who…

  16. Total Quality Management: Statistics and Graphics III - Experimental Design and Taguchi Methods. AIR 1993 Annual Forum Paper.

    ERIC Educational Resources Information Center

    Schwabe, Robert A.

    Interest in Total Quality Management (TQM) at institutions of higher education has been stressed in recent years as an important area of activity for institutional researchers. Two previous AIR Forum papers have presented some of the statistical and graphical methods used for TQM. This paper, the third in the series, first discusses some of the…

  17. Eliminating the influence of serial correlation on statistical process control charts using trend free pre-whitening (TFPW) method

    NASA Astrophysics Data System (ADS)

    Desa, Nor Hasliza Mat; Jemain, Abdul Aziz

    2013-11-01

    A key assumption in traditional statistical process control (SPC) technique is based on the requirement that observations or time series data are normally and independently distributed. The presences of a serial autocorrelation results in a number of problems, including an increase in the type I error rate and thereby increase the expected number of false alarm in the process observation. However, the independency assumption is often violated in practice due to the influence of serial correlation in the observation. Therefore, the aim of this paper is to demonstrate with the hospital admission data, the influence of serial correlation on the statistical control charts. The trend free pre-whitening (TFPW) method has been used and applied as an alternative method to obtain residuals series which are statistically uncorrelated to each other. In this study, a data set of daily hospital admission for respiratory and cardiovascular diseases was used from the period of 1 January 2009 to 31 December 2009 (365 days). Result showed that TFPW method is an easy and useful method in removing the influence of serial correlation from the hospital admission data. It can be concluded that statistical control chart based on residual series perform better compared to original hospital admission series which influenced by the effects of serial correlation data.

  18. Research Design and Statistical Methods in Indian Medical Journals: A Retrospective Survey

    PubMed Central

    Hassan, Shabbeer; Yellur, Rajashree; Subramani, Pooventhan; Adiga, Poornima; Gokhale, Manoj; Iyer, Manasa S.; Mayya, Shreemathi S.

    2015-01-01

    Good quality medical research generally requires not only an expertise in the chosen medical field of interest but also a sound knowledge of statistical methodology. The number of medical research articles which have been published in Indian medical journals has increased quite substantially in the past decade. The aim of this study was to collate all evidence on study design quality and statistical analyses used in selected leading Indian medical journals. Ten (10) leading Indian medical journals were selected based on impact factors and all original research articles published in 2003 (N = 588) and 2013 (N = 774) were categorized and reviewed. A validated checklist on study design, statistical analyses, results presentation, and interpretation was used for review and evaluation of the articles. Main outcomes considered in the present study were – study design types and their frequencies, error/defects proportion in study design, statistical analyses, and implementation of CONSORT checklist in RCT (randomized clinical trials). From 2003 to 2013: The proportion of erroneous statistical analyses did not decrease (χ2=0.592, Φ=0.027, p=0.4418), 25% (80/320) in 2003 compared to 22.6% (111/490) in 2013. Compared with 2003, significant improvement was seen in 2013; the proportion of papers using statistical tests increased significantly (χ2=26.96, Φ=0.16, p<0.0001) from 42.5% (250/588) to 56.7 % (439/774). The overall proportion of errors in study design decreased significantly (χ2=16.783, Φ=0.12 p<0.0001), 41.3% (243/588) compared to 30.6% (237/774). In 2013, randomized clinical trials designs has remained very low (7.3%, 43/588) with majority showing some errors (41 papers, 95.3%). Majority of the published studies were retrospective in nature both in 2003 [79.1% (465/588)] and in 2013 [78.2% (605/774)]. Major decreases in error proportions were observed in both results presentation (χ2=24.477, Φ=0.17, p<0.0001), 82.2% (263/320) compared to 66.3% (325

  19. A new method to reduce the statistical and systematic uncertainty of chance coincidence backgrounds measured with waveform digitizers

    NASA Astrophysics Data System (ADS)

    O`Donnell, J. M.

    2016-01-01

    A new method for measuring chance-coincidence backgrounds during the collection of coincidence data is presented. The method relies on acquiring data with near-zero dead time, which is now realistic due to the increasing deployment of flash electronic-digitizer (waveform digitizer) techniques. An experiment designed to use this new method is capable of acquiring more coincidence data, and a much reduced statistical fluctuation of the measured background. A statistical analysis is presented, and used to derive a figure of merit for the new method. Factors of four improvement over other analyzes are realistic. The technique is illustrated with preliminary data taken as part of a program to make new measurements of the prompt fission neutron spectra at Los Alamos Neutron Science Center. It is expected that the these measurements will occur in a regime where the maximum figure of merit will be exploited.

  20. Are PPS payments adequate? Issues for updating and assessing rates

    PubMed Central

    Sheingold, Steven H.; Richter, Elizabeth

    1992-01-01

    Declining operating margins under Medicare's prospective payment system (PPS) have focused attention on the adequacy of payment rates. The question of whether annual updates to the rates have been too low or cost increases too high has become important. In this article we discuss issues relevant to updating PPS rates and judging their adequacy. We describe a modification to the current framework for recommending annual update factors. This framework is then used to retrospectively assess PPS payment and cost growth since 1985. The preliminary results suggest that current rates are more than adequate to support the cost of efficient care. Also discussed are why using financial margins to evaluate rates is problematic and alternative methods that might be employed. PMID:10127450

  1. Dynamics of statistically confident particle sizes and concentrations in blood plasma obtained by the dynamic light scattering method

    NASA Astrophysics Data System (ADS)

    Chaikov, Leonid L.; Kirichenko, Marina N.; Krivokhizha, Svetlana V.; Zaritskiy, Alexander R.

    2015-05-01

    The work is devoted to the study of sizes and concentrations of proteins, and their aggregates in blood plasma samples, using static and dynamic light scattering methods. A new approach is proposed based on multiple repetition of measurements of intensity size distribution and on counting the number of registrations of different sizes, which made it possible to obtain statistically confident particle sizes and concentrations in the blood plasma. It was revealed that statistically confident particle sizes in the blood plasma were stable during 30 h of observations, whereas the concentrations of particles of different sizes varied as a result of redistribution of material between them owing to the protein degradation processes.

  2. Statistical methods for estimating normal blood chemistry ranges and variance in rainbow trout (Salmo gairdneri), Shasta Strain

    USGS Publications Warehouse

    Wedemeyer, Gary A.; Nelson, Nancy C.

    1975-01-01

    Gaussian and nonparametric (percentile estimate and tolerance interval) statistical methods were used to estimate normal ranges for blood chemistry (bicarbonate, bilirubin, calcium, hematocrit, hemoglobin, magnesium, mean cell hemoglobin concentration, osmolality, inorganic phosphorus, and pH for juvenile rainbow (Salmo gairdneri, Shasta strain) trout held under defined environmental conditions. The percentile estimate and Gaussian methods gave similar normal ranges, whereas the tolerance interval method gave consistently wider ranges for all blood variables except hemoglobin. If the underlying frequency distribution is unknown, the percentile estimate procedure would be the method of choice.

  3. Methods of mathematical statistics for verification of hydrogen content in zirconium hydride moderator

    SciTech Connect

    Ponomarev-Stepnoi, N.N.; Bubelev, V.G.; Glushkov, Ye.S.; Kompaniets, G.V.; Nosov, V.I. )

    1995-02-01

    The hydrogen content of zirconium hydride blocks used as the moderator in Topaz-2-type space reactors is estimated according to correlation-regression analysis procedures of mathematical statistics and is based on the results of the definition of the reactivity of the blocks in a research critical assembly. A linear mathematical model for a variable response is formulated within the framework of the first-order perturbation theory applied to the estimation of reactivity effects in reactors. A PASPORT computer code is written based on the developed algorithm. The statistical analysis of the available data performed by using PASPORT shows that the developed approach allows determination of the insignificance of the contribution of the impurities to the reactivity of the blocks, verification of the manufacturer's data on the hydrogen content in zirconium hydride blocks, and estimation of the reactivity shift in a standard block.

  4. Predictability of the recent slowdown and subsequent recovery of large-scale surface warming using statistical methods

    NASA Astrophysics Data System (ADS)

    Mann, Michael E.; Steinman, Byron A.; Miller, Sonya K.; Frankcombe, Leela M.; England, Matthew H.; Cheung, Anson H.

    2016-04-01

    The temporary slowdown in large-scale surface warming during the early 2000s has been attributed to both external and internal sources of climate variability. Using semiempirical estimates of the internal low-frequency variability component in Northern Hemisphere, Atlantic, and Pacific surface temperatures in concert with statistical hindcast experiments, we investigate whether the slowdown and its recent recovery were predictable. We conclude that the internal variability of the North Pacific, which played a critical role in the slowdown, does not appear to have been predictable using statistical forecast methods. An additional minor contribution from the North Atlantic, by contrast, appears to exhibit some predictability. While our analyses focus on combining semiempirical estimates of internal climatic variability with statistical hindcast experiments, possible implications for initialized model predictions are also discussed.

  5. Systematic analysis of coding and noncoding DNA sequences using methods of statistical linguistics

    NASA Technical Reports Server (NTRS)

    Mantegna, R. N.; Buldyrev, S. V.; Goldberger, A. L.; Havlin, S.; Peng, C. K.; Simons, M.; Stanley, H. E.

    1995-01-01

    We compare the statistical properties of coding and noncoding regions in eukaryotic and viral DNA sequences by adapting two tests developed for the analysis of natural languages and symbolic sequences. The data set comprises all 30 sequences of length above 50 000 base pairs in GenBank Release No. 81.0, as well as the recently published sequences of C. elegans chromosome III (2.2 Mbp) and yeast chromosome XI (661 Kbp). We find that for the three chromosomes we studied the statistical properties of noncoding regions appear to be closer to those observed in natural languages than those of coding regions. In particular, (i) a n-tuple Zipf analysis of noncoding regions reveals a regime close to power-law behavior while the coding regions show logarithmic behavior over a wide interval, while (ii) an n-gram entropy measurement shows that the noncoding regions have a lower n-gram entropy (and hence a larger "n-gram redundancy") than the coding regions. In contrast to the three chromosomes, we find that for vertebrates such as primates and rodents and for viral DNA, the difference between the statistical properties of coding and noncoding regions is not pronounced and therefore the results of the analyses of the investigated sequences are less conclusive. After noting the intrinsic limitations of the n-gram redundancy analysis, we also briefly discuss the failure of the zeroth- and first-order Markovian models or simple nucleotide repeats to account fully for these "linguistic" features of DNA. Finally, we emphasize that our results by no means prove the existence of a "language" in noncoding DNA.

  6. A Procedure for Statistical Downscaling of Precipitation with an Objective Method for Predictor Selection

    NASA Astrophysics Data System (ADS)

    Najafi, M.; Moradkhani, H.; Wherry, S.

    2009-12-01

    Downscaling General Circulation Models’ (GCM) outputs to a finer grid cell size is an important step in climate change impact and adaptation studies in particular for hydrologic applications. Many investigations have been focused on presenting techniques to downscale GCM data utilizing statistical approaches. Nevertheless there is currently the need to present techniques on predictor selection and also to compare different downscaling models’ capabilities. Hence in this study an algorithm has been developed to select GCM predictors in a subseasonal to seasonal time scale. Independent component analysis was used to find the statistically independent signals of CGCM3 variables in the 4*7 grid cells covering the Willamette river basin in Oregon, USA. Using the multi-linear regression cross validation (MLR-CV) the GCM predictors were selected for each period. The selected predictors were then applied to train the ANFIS (Adaptive Network-based Fuzzy Inference System) and the SVM (Support Vector Machine) models, and their performances were assessed on the test data. To design more robust networks that are less dependent on training data set, the cross validation was performed. . Predictors with the best performance for each season in the test set (using both ANFIS and SVM models) were selected for that specific season. The comparison of ANFIS and SVM models using statistical measures showed that ANFIS presents better results suitable for climate impact studies. Also application of ICA allowed reducing the size of many dependent GCM variables in 28 grid cells considerably resulting in higher accuracy in downscaling and more effectiveness in the procedure.

  7. The application of time series forecasting methods to an estimation problem using provisional mortality statistics.

    PubMed

    Katzoff, M

    1989-03-01

    Provisional estimates of mortality for selected causes of death are published each month by the National Center for Health Statistics. These estimates are based upon a ten per cent sample of death certificates in the United States. Final mortality results, based upon all the death certificates for a calendar year, are available one to two years after publication of the provisional estimates. This paper explores the potential of time series forecasting techniques for improving mortality estimates by using the correlation structure between the provisional and final series to obtain mortality estimates that are expected to be closer to final values than currently used provisional estimates. PMID:2711064

  8. An Investigation of the Overlap Between the Statistical Discrete Gust and the Power Spectral Density Analysis Methods

    NASA Technical Reports Server (NTRS)

    Perry, Boyd, III; Pototzky, Anthony S.; Woods, Jessica A.

    1989-01-01

    The results of a NASA investigation of a claimed Overlap between two gust response analysis methods: the Statistical Discrete Gust (SDG) Method and the Power Spectral Density (PSD) Method are presented. The claim is that the ratio of an SDG response to the corresponding PSD response is 10.4. Analytical results presented for several different airplanes at several different flight conditions indicate that such an Overlap does appear to exist. However, the claim was not met precisely: a scatter of up to about 10 percent about the 10.4 factor can be expected.

  9. An investigation of the 'Overlap' between the Statistical-Discrete-Gust and the Power-Spectral-Density analysis methods

    NASA Technical Reports Server (NTRS)

    Perry, Boyd, III; Pototzky, Anthony S.; Woods, Jessica A.

    1989-01-01

    This paper presents the results of a NASA investigation of a claimed 'Overlap' between two gust response analysis methods: the Statistical Discrete Gust (SDG) method and the Power Spectral Density (PSD) method. The claim is that the ratio of an SDG response to the corresponding PSD response is 10.4. Analytical results presented in this paper for several different airplanes at several different flight conditions indicate that such an 'Overlap' does appear to exist. However, the claim was not met precisely: a scatter of up to about 10 percent about the 10.4 factor can be expected.

  10. The Fusion of Financial Analysis and Seismology: Statistical Methods from Financial Market Analysis Applied to Earthquake Data

    NASA Astrophysics Data System (ADS)

    Ohyanagi, S.; Dileonardo, C.

    2013-12-01

    As a natural phenomenon earthquake occurrence is difficult to predict. Statistical analysis of earthquake data was performed using candlestick chart and Bollinger Band methods. These statistical methods, commonly used in the financial world to analyze market trends were tested against earthquake data. Earthquakes above Mw 4.0 located on shore of Sanriku (37.75°N ~ 41.00°N, 143.00°E ~ 144.50°E) from February 1973 to May 2013 were selected for analysis. Two specific patterns in earthquake occurrence were recognized through the analysis. One is a spread of candlestick prior to the occurrence of events greater than Mw 6.0. A second pattern shows convergence in the Bollinger Band, which implies a positive or negative change in the trend of earthquakes. Both patterns match general models for the buildup and release of strain through the earthquake cycle, and agree with both the characteristics of the candlestick chart and Bollinger Band analysis. These results show there is a high correlation between patterns in earthquake occurrence and trend analysis by these two statistical methods. The results of this study agree with the appropriateness of the application of these financial analysis methods to the analysis of earthquake occurrence.

  11. STATISTICAL VALIDATION OF SULFATE QUANTIFICATION METHODS USED FOR ANALYSIS OF ACID MINE DRAINAGE

    EPA Science Inventory

    Turbidimetric method (TM), ion chromatography (IC) and inductively coupled plasma atomic emission spectrometry (ICP-AES) with and without acid digestion have been compared and validated for the determination of sulfate in mining wastewater. Analytical methods were chosen to compa...

  12. Large scale wildlife monitoring studies: statistical methods for design and analysis

    USGS Publications Warehouse

    Pollock, K.H.; Nichols, J.D.; Simons, T.R.; Farnsworth, G.L.; Bailey, L.L.; Sauer, J.R.

    2002-01-01

    Techniques for estimation of absolute abundance of wildlife populations have received a lot of attention in recent years. The statistical research has been focused on intensive small-scale studies. Recently, however, wildlife biologists have desired to study populations of animals at very large scales for monitoring purposes. Population indices are widely used in these extensive monitoring programs because they are inexpensive compared to estimates of absolute abundance. A crucial underlying assumption is that the population index (C) is directly proportional to the population density (D). The proportionality constant, b, is simply the probability of 'detection' for animals in the survey. As spatial and temporal comparisons of indices are crucial, it is necessary to also assume that the probability of detection is constant over space and time. Biologists intuitively recognize this when they design rigid protocols for the studies where the indices are collected. Unfortunately, however in many field studios the assumption is clearly invalid. We believe that the estimation of detection probability should be built into the monitoring design through a double sampling approach. A large sample of points provides an abundance index, and a smaller sub-sample of the same points is used to estimate detection probability. There is an important need for statistical research on the design and analysis of these complex studies. Some basic concepts based on actual avian, amphibian, and fish monitoring studies are presented in this article.

  13. Automated microcalcification detection in mammograms using statistical variable-box-threshold filter method

    NASA Astrophysics Data System (ADS)

    Wilson, Mark; Mitra, Sunanda; Roberson, Glenn H.; Shieh, Yao-Yang

    1997-10-01

    Currently early detection of breast cancer is primarily accomplished by mammography and suspicious findings may lead to a decision for performing a biopsy. Digital enhancement and pattern recognition techniques may aid in early detection of some patterns such as microcalcification clusters indicating onset of DCIS (ductal carcinoma in situ) that accounts for 20% of all mammographically detected breast cancers and could be treated when detected early. These individual calcifications are hard to detect due to size and shape variability and inhomogeneous background texture. Our study addresses only early detection of microcalcifications that allows the radiologist to interpret the x-ray findings in computer-aided enhanced form easier than evaluating the x-ray film directly. We present an algorithm which locates microcalcifications based on local grayscale variability and of tissue structures and image statistics. Threshold filters with lower and upper bounds computed from the image statistics of the entire image and selected subimages were designed to enhance the entire image. This enhanced image was used as the initial image for identifying the micro-calcifications based on the variable box threshold filters at different resolutions. The test images came from the Texas Tech University Health Sciences Center and the MIAS mammographic database, which are classified into various categories including microcalcifications. Classification of other types of abnormalities in mammograms based on their characteristic features is addressed in later studies.

  14. Identification of robust statistical downscaling methods based on a comprehensive suite of performance metrics for South Korea

    NASA Astrophysics Data System (ADS)

    Eum, H. I.; Cannon, A. J.

    2015-12-01

    Climate models are a key provider to investigate impacts of projected future climate conditions on regional hydrologic systems. However, there is a considerable mismatch of spatial resolution between GCMs and regional applications, in particular a region characterized by complex terrain such as Korean peninsula. Therefore, a downscaling procedure is an essential to assess regional impacts of climate change. Numerous statistical downscaling methods have been used mainly due to the computational efficiency and simplicity. In this study, four statistical downscaling methods [Bias-Correction/Spatial Disaggregation (BCSD), Bias-Correction/Constructed Analogue (BCCA), Multivariate Adaptive Constructed Analogs (MACA), and Bias-Correction/Climate Imprint (BCCI)] are applied to downscale the latest Climate Forecast System Reanalysis data to stations for precipitation, maximum temperature, and minimum temperature over South Korea. By split sampling scheme, all methods are calibrated with observational station data for 19 years from 1973 to 1991 are and tested for the recent 19 years from 1992 to 2010. To assess skill of the downscaling methods, we construct a comprehensive suite of performance metrics that measure an ability of reproducing temporal correlation, distribution, spatial correlation, and extreme events. In addition, we employ Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) to identify robust statistical downscaling methods based on the performance metrics for each season. The results show that downscaling skill is considerably affected by the skill of CFSR and all methods lead to large improvements in representing all performance metrics. According to seasonal performance metrics evaluated, when TOPSIS is applied, MACA is identified as the most reliable and robust method for all variables and seasons. Note that such result is derived from CFSR output which is recognized as near perfect climate data in climate studies. Therefore, the

  15. The Kernel Method of Equating Score Distributions. Program Statistics Research Technical Report No. 89-84.

    ERIC Educational Resources Information Center

    Holland, Paul W.; Thayer, Dorothy T.

    A new and unified approach to test equating is described that is based on log-linear models for smoothing score distributions and on the kernel method of nonparametric density estimation. The new method contains both linear and standard equipercentile methods as special cases and can handle several important equating data collection designs. An…

  16. 7 CFR 4290.200 - Adequate capital for RBICs.

    Code of Federal Regulations, 2011 CFR

    2011-01-01

    ... 7 Agriculture 15 2011-01-01 2011-01-01 false Adequate capital for RBICs. 4290.200 Section 4290.200 Agriculture Regulations of the Department of Agriculture (Continued) RURAL BUSINESS-COOPERATIVE SERVICE AND... Qualifications for the RBIC Program Capitalizing A Rbic § 4290.200 Adequate capital for RBICs. You must meet...

  17. 13 CFR 107.200 - Adequate capital for Licensees.

    Code of Federal Regulations, 2011 CFR

    2011-01-01

    ... 13 Business Credit and Assistance 1 2011-01-01 2011-01-01 false Adequate capital for Licensees... INVESTMENT COMPANIES Qualifying for an SBIC License Capitalizing An Sbic § 107.200 Adequate capital for... Licensee, and to receive Leverage. (a) You must have enough Regulatory Capital to provide...

  18. 13 CFR 107.200 - Adequate capital for Licensees.

    Code of Federal Regulations, 2010 CFR

    2010-01-01

    ... 13 Business Credit and Assistance 1 2010-01-01 2010-01-01 false Adequate capital for Licensees... INVESTMENT COMPANIES Qualifying for an SBIC License Capitalizing An Sbic § 107.200 Adequate capital for... Licensee, and to receive Leverage. (a) You must have enough Regulatory Capital to provide...

  19. 7 CFR 4290.200 - Adequate capital for RBICs.

    Code of Federal Regulations, 2010 CFR

    2010-01-01

    ... 7 Agriculture 15 2010-01-01 2010-01-01 false Adequate capital for RBICs. 4290.200 Section 4290.200 Agriculture Regulations of the Department of Agriculture (Continued) RURAL BUSINESS-COOPERATIVE SERVICE AND... Qualifications for the RBIC Program Capitalizing A Rbic § 4290.200 Adequate capital for RBICs. You must meet...

  20. 10 CFR 1304.114 - Responsibility for maintaining adequate safeguards.

    Code of Federal Regulations, 2011 CFR

    2011-01-01

    ... 10 Energy 4 2011-01-01 2011-01-01 false Responsibility for maintaining adequate safeguards. 1304.114 Section 1304.114 Energy NUCLEAR WASTE TECHNICAL REVIEW BOARD PRIVACY ACT OF 1974 § 1304.114 Responsibility for maintaining adequate safeguards. The Board has the responsibility for maintaining...

  1. 40 CFR 716.25 - Adequate file search.

    Code of Federal Regulations, 2010 CFR

    2010-07-01

    ... 40 Protection of Environment 30 2010-07-01 2010-07-01 false Adequate file search. 716.25 Section 716.25 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) TOXIC SUBSTANCES CONTROL ACT HEALTH AND SAFETY DATA REPORTING General Provisions § 716.25 Adequate file search. The scope of...

  2. 40 CFR 51.354 - Adequate tools and resources.

    Code of Federal Regulations, 2011 CFR

    2011-07-01

    ... 40 Protection of Environment 2 2011-07-01 2011-07-01 false Adequate tools and resources. 51.354... Requirements § 51.354 Adequate tools and resources. (a) Administrative resources. The program shall maintain the administrative resources necessary to perform all of the program functions including...

  3. 40 CFR 51.354 - Adequate tools and resources.

    Code of Federal Regulations, 2012 CFR

    2012-07-01

    ... 40 Protection of Environment 2 2012-07-01 2012-07-01 false Adequate tools and resources. 51.354... Requirements § 51.354 Adequate tools and resources. (a) Administrative resources. The program shall maintain the administrative resources necessary to perform all of the program functions including...

  4. 40 CFR 51.354 - Adequate tools and resources.

    Code of Federal Regulations, 2014 CFR

    2014-07-01

    ... 40 Protection of Environment 2 2014-07-01 2014-07-01 false Adequate tools and resources. 51.354... Requirements § 51.354 Adequate tools and resources. (a) Administrative resources. The program shall maintain the administrative resources necessary to perform all of the program functions including...

  5. 40 CFR 51.354 - Adequate tools and resources.

    Code of Federal Regulations, 2013 CFR

    2013-07-01

    ... 40 Protection of Environment 2 2013-07-01 2013-07-01 false Adequate tools and resources. 51.354... Requirements § 51.354 Adequate tools and resources. (a) Administrative resources. The program shall maintain the administrative resources necessary to perform all of the program functions including...

  6. 40 CFR 716.25 - Adequate file search.

    Code of Federal Regulations, 2011 CFR

    2011-07-01

    ... 40 Protection of Environment 31 2011-07-01 2011-07-01 false Adequate file search. 716.25 Section... ACT HEALTH AND SAFETY DATA REPORTING General Provisions § 716.25 Adequate file search. The scope of a person's responsibility to search records is limited to records in the location(s) where the...

  7. 40 CFR 716.25 - Adequate file search.

    Code of Federal Regulations, 2013 CFR

    2013-07-01

    ... 40 Protection of Environment 32 2013-07-01 2013-07-01 false Adequate file search. 716.25 Section... ACT HEALTH AND SAFETY DATA REPORTING General Provisions § 716.25 Adequate file search. The scope of a person's responsibility to search records is limited to records in the location(s) where the...

  8. 40 CFR 716.25 - Adequate file search.

    Code of Federal Regulations, 2014 CFR

    2014-07-01

    ... 40 Protection of Environment 31 2014-07-01 2014-07-01 false Adequate file search. 716.25 Section... ACT HEALTH AND SAFETY DATA REPORTING General Provisions § 716.25 Adequate file search. The scope of a person's responsibility to search records is limited to records in the location(s) where the...

  9. 40 CFR 716.25 - Adequate file search.

    Code of Federal Regulations, 2012 CFR

    2012-07-01

    ... 40 Protection of Environment 32 2012-07-01 2012-07-01 false Adequate file search. 716.25 Section... ACT HEALTH AND SAFETY DATA REPORTING General Provisions § 716.25 Adequate file search. The scope of a person's responsibility to search records is limited to records in the location(s) where the...

  10. 10 CFR 1304.114 - Responsibility for maintaining adequate safeguards.

    Code of Federal Regulations, 2014 CFR

    2014-01-01

    ... 10 Energy 4 2014-01-01 2014-01-01 false Responsibility for maintaining adequate safeguards. 1304.114 Section 1304.114 Energy NUCLEAR WASTE TECHNICAL REVIEW BOARD PRIVACY ACT OF 1974 § 1304.114 Responsibility for maintaining adequate safeguards. The Board has the responsibility for maintaining...

  11. 10 CFR 1304.114 - Responsibility for maintaining adequate safeguards.

    Code of Federal Regulations, 2013 CFR

    2013-01-01

    ... 10 Energy 4 2013-01-01 2013-01-01 false Responsibility for maintaining adequate safeguards. 1304.114 Section 1304.114 Energy NUCLEAR WASTE TECHNICAL REVIEW BOARD PRIVACY ACT OF 1974 § 1304.114 Responsibility for maintaining adequate safeguards. The Board has the responsibility for maintaining...

  12. 10 CFR 503.35 - Inability to obtain adequate capital.

    Code of Federal Regulations, 2010 CFR

    2010-01-01

    ... 10 Energy 4 2010-01-01 2010-01-01 false Inability to obtain adequate capital. 503.35 Section 503.35 Energy DEPARTMENT OF ENERGY (CONTINUED) ALTERNATE FUELS NEW FACILITIES Permanent Exemptions for New Facilities § 503.35 Inability to obtain adequate capital. (a) Eligibility. Section 212(a)(1)(D)...

  13. 10 CFR 503.35 - Inability to obtain adequate capital.

    Code of Federal Regulations, 2011 CFR

    2011-01-01

    ... 10 Energy 4 2011-01-01 2011-01-01 false Inability to obtain adequate capital. 503.35 Section 503.35 Energy DEPARTMENT OF ENERGY (CONTINUED) ALTERNATE FUELS NEW FACILITIES Permanent Exemptions for New Facilities § 503.35 Inability to obtain adequate capital. (a) Eligibility. Section 212(a)(1)(D)...

  14. 15 CFR 970.404 - Adequate exploration plan.

    Code of Federal Regulations, 2011 CFR

    2011-01-01

    ... ENVIRONMENTAL DATA SERVICE DEEP SEABED MINING REGULATIONS FOR EXPLORATION LICENSES Certification of Applications § 970.404 Adequate exploration plan. Before he may certify an application, the Administrator must find... 15 Commerce and Foreign Trade 3 2011-01-01 2011-01-01 false Adequate exploration plan....

  15. 15 CFR 970.404 - Adequate exploration plan.

    Code of Federal Regulations, 2010 CFR

    2010-01-01

    ... ENVIRONMENTAL DATA SERVICE DEEP SEABED MINING REGULATIONS FOR EXPLORATION LICENSES Certification of Applications § 970.404 Adequate exploration plan. Before he may certify an application, the Administrator must find... 15 Commerce and Foreign Trade 3 2010-01-01 2010-01-01 false Adequate exploration plan....

  16. "Something Adequate"? In Memoriam Seamus Heaney, Sister Quinlan, Nirbhaya

    ERIC Educational Resources Information Center

    Parker, Jan

    2014-01-01

    Seamus Heaney talked of poetry's responsibility to represent the "bloody miracle", the "terrible beauty" of atrocity; to create "something adequate". This article asks, what is adequate to the burning and eating of a nun and the murderous gang rape and evisceration of a medical student? It considers Njabulo…

  17. A new modeling and simulation method for important statistical performance prediction of single photon avalanche diode detectors

    NASA Astrophysics Data System (ADS)

    Xu, Yue; Xiang, Ping; Xie, Xiaopeng; Huang, Yang

    2016-06-01

    This paper presents a new modeling and simulation method to predict the important statistical performance of single photon avalanche diode (SPAD) detectors, including photon detection efficiency (PDE), dark count rate (DCR) and afterpulsing probability (AP). Three local electric field models are derived for the PDE, DCR and AP calculations, which show analytical dependence of key parameters such as avalanche triggering probability, impact ionization rate and electric field distributions that can be directly obtained from Geiger mode Technology Computer Aided Design (TCAD) simulation. The model calculation results are proven to be in good agreement with the reported experimental data in the open literature, suggesting that the proposed modeling and simulation method is very suitable for the prediction of SPAD statistical performance.

  18. Preparing systems engineering and computing science students in disciplined methods, quantitative, and advanced statistical techniques to improve process performance

    NASA Astrophysics Data System (ADS)

    McCray, Wilmon Wil L., Jr.

    The research was prompted by a need to conduct a study that assesses process improvement, quality management and analytical techniques taught to students in U.S. colleges and universities undergraduate and graduate systems engineering and the computing science discipline (e.g., software engineering, computer science, and information technology) degree programs during their academic training that can be applied to quantitatively manage processes for performance. Everyone involved in executing repeatable processes in the software and systems development lifecycle processes needs to become familiar with the concepts of quantitative management, statistical thinking, process improvement methods and how they relate to process-performance. Organizations are starting to embrace the de facto Software Engineering Institute (SEI) Capability Maturity Model Integration (CMMI RTM) Models as process improvement frameworks to improve business processes performance. High maturity process areas in the CMMI model imply the use of analytical, statistical, quantitative management techniques, and process performance modeling to identify and eliminate sources of variation, continually improve process-performance; reduce cost and predict future outcomes. The research study identifies and provides a detail discussion of the gap analysis findings of process improvement and quantitative analysis techniques taught in U.S. universities systems engineering and computing science degree programs, gaps that exist in the literature, and a comparison analysis which identifies the gaps that exist between the SEI's "healthy ingredients " of a process performance model and courses taught in U.S. universities degree program. The research also heightens awareness that academicians have conducted little research on applicable statistics and quantitative techniques that can be used to demonstrate high maturity as implied in the CMMI models. The research also includes a Monte Carlo simulation optimization

  19. Incorrect statistical method in parallel-groups RCT led to unsubstantiated conclusions.

    PubMed

    Allison, David B; Antoine, Lisa H; George, Brandon J

    2016-01-01

    The article by Aiso et al. titled "Compared with the intake of commercial vegetable juice, the intake of fresh fruit and komatsuna (Brassica rapa L. var perviridis) juice mixture reduces serum cholesterol in middle-aged men: a randomized controlled pilot study" does not meet the expected standards of Lipids in Health and Disease. Although the article concludes that there are some significant benefits to their komatsuna juice mixture, these claims are not supported by the statistical analyses used. An incorrect procedure was used to compare the differences in two treatment groups over time, and a large number of outcomes were tested without correction; both issues are known to produce high rates of false positives, making the conclusions of the study unjustified. The study also fails to follow published journal standards regarding clinical trial registration and reporting. PMID:27083538

  20. Device oriented statistical modeling method for process variability in 45nm analog CMOS technology

    NASA Astrophysics Data System (ADS)

    Ajayan, K. R.; Bhat, Navakanta

    2012-10-01

    With the rapid scaling down of the semiconductor process technology, the process variation aware circuit design has become essential today. Several statistical models have been proposed to deal with the process variation. We propose an accurate BSIM model for handling variability in 45nm CMOS technology. The MOSFET is designed to meet the specification of low standby power technology of International Technology Roadmap for Semiconductors (ITRS).The process parameters variation of annealing temperature, oxide thickness, halo dose and title angle of halo implant are considered for the model development. One parameter variation at a time is considered for developing the model. The model validation is done by performance matching with device simulation results and reported error is less than 10%.

  1. Statistical stage transition detection method for small sample gene expression time series data.

    PubMed

    Tominaga, Daisuke

    2014-08-01

    In terms of their internal (genetic) and external (phenotypic) states, living cells are always changing at varying rates. Periods of stable or low rate of change are often called States, Stages, or Phases, whereas high-rate periods are called Transitions or Transients. While states and transitions are observed phenotypically, such as cell differentiation, cancer progression, for example, are related with gene expression levels. On the other hand, stages of gene expression are definable based on changes of expression levels. Analyzing relations between state changes of phenotypes and stage transitions of gene expression levels is a general approach to elucidate mechanisms of life phenomena. Herein, we propose an algorithm to detect stage transitions in a time series of expression levels of a gene by defining statistically optimal division points. The algorithm shows detecting ability for simulated datasets. An annotation based analysis on detecting results for a dataset of initial development of Caenorhabditis elegans agrees with that are presented in the literature. PMID:24960588

  2. Computational and statistical methods for high-throughput analysis of post-translational modifications of proteins.

    PubMed

    Schwämmle, Veit; Verano-Braga, Thiago; Roepstorff, Peter

    2015-11-01

    The investigation of post-translational modifications (PTMs) represents one of the main research focuses for the study of protein function and cell signaling. Mass spectrometry instrumentation with increasing sensitivity improved protocols for PTM enrichment and recently established pipelines for high-throughput experiments allow large-scale identification and quantification of several PTM types. This review addresses the concurrently emerging challenges for the computational analysis of the resulting data and presents PTM-centered approaches for spectra identification, statistical analysis, multivariate analysis and data interpretation. We furthermore discuss the potential of future developments that will help to gain deep insight into the PTM-ome and its biological role in cells. This article is part of a Special Issue entitled: Computational Proteomics. PMID:26216596

  3. Adequate peritoneal dialysis: theoretical model and patient treatment.

    PubMed

    Tast, C

    1998-01-01

    The objective of this study was to evaluate the relationship between adequate PD with sufficient weekly Kt/V (2.0) and Creatinine clearance (CCR) (60l) and necessary daily dialysate volume. This recommended parameter was the result of a recent multi-centre study (CANUSA). For this there were 40 patients in our hospital examined and compared in 1996, who carried out PD for at least 8 weeks and up to 6 years. These goals (CANUSA) are easily attainable in the early treatment of many individuals with a low body surface area (BSA). With higher BSA or missing RRF (Residual Renal Function) the daily dose of dialysis must be adjusted. We found it difficult to obtain the recommended parameters and tried to find a solution to this problem. The simplest method is to increase the volume or exchange rate. The most expensive method is to change from CAPD to APD with the possibility of higher volume or exchange rates. Selection of therapy must take into consideration: 1. patient preference, 2. body mass, 3. peritoneal transport rates, 4. ability to perform therapy, 5. cost of therapy and 6. risk of peritonitis. With this information in mind, an individual prescription can be formulated and matched to the appropriate modality of PD. PMID:10392062

  4. Delineation of Surface-Groundwater Interactions Using Statistical Analysis of Temperature Time-Series and Resistivity Methods

    NASA Astrophysics Data System (ADS)

    Scotch, C. G.; Murgulet, D.; Hay, R.

    2013-12-01

    Although surface-water and groundwater are often referred to as separate domains, they are intimately related as a change in one domain can ultimately affect the other domain. Since the two domains act as linked pathways for contaminant transport in the hydrologic cycle a comprehensive understanding of this relationship is essential for improved SW-GW management practices. The main objective of this study is to develop new statistical methods to better identify and characterize the advective component or water movement between SW-GW in a coastal area along the South Texas coast, adjacent to the Gulf of Mexico (GOM) margin, characterized by low gradients and low-conductivity stream beds. Identifying advection zones using temperature data in regions with low topographic relief and numerous small-scale flow paths is difficult. To overcome this challenge this study proposes the use of seasonal-trend decomposition (STL) of time series temperature data to analyze exchanges in this type of environment. Seasonal decomposition analysis was used to remove the daily and annual cyclic components leaving the random or non-cyclic component. It can be inferred that high variances of the random component indicate periods of advection. This statistically-derived advective component correlates well with advection periods identified from the conventional time-series temperature profile analysis. This correlation is a good validation of the statistical approach as means of identifying periods of advection and SW-GW interaction. Electrical resistivity imaging will be used for validation of the statistical model.

  5. Statistics Clinic

    NASA Technical Reports Server (NTRS)

    Feiveson, Alan H.; Foy, Millennia; Ploutz-Snyder, Robert; Fiedler, James

    2014-01-01

    Do you have elevated p-values? Is the data analysis process getting you down? Do you experience anxiety when you need to respond to criticism of statistical methods in your manuscript? You may be suffering from Insufficient Statistical Support Syndrome (ISSS). For symptomatic relief of ISSS, come for a free consultation with JSC biostatisticians at our help desk during the poster sessions at the HRP Investigators Workshop. Get answers to common questions about sample size, missing data, multiple testing, when to trust the results of your analyses and more. Side effects may include sudden loss of statistics anxiety, improved interpretation of your data, and increased confidence in your results.

  6. Statistical methods in detecting differential expressed genes, analyzing insertion tolerance for genes and group selection for survival data

    NASA Astrophysics Data System (ADS)

    Liu, Fangfang

    The thesis is composed of three independent projects: (i) analyzing transposon-sequencing data to infer functions of genes on bacteria growth (chapter 2), (ii) developing semi-parametric Bayesian method for differential gene expression analysis with RNA-sequencing data (chapter 3), (iii) solving group selection problem for survival data (chapter 4). All projects are motivated by statistical challenges raised in biological research. The first project is motivated by the need to develop statistical models to accommodate the transposon insertion sequencing (Tn-Seq) data, Tn-Seq data consist of sequence reads around each transposon insertion site. The detection of transposon insertion at a given site indicates that the disruption of genomic sequence at this site does not cause essential function loss and the bacteria can still grow. Hence, such measurements have been used to infer the functions of each gene on bacteria growth. We propose a zero-inflated Poisson regression method for analyzing the Tn-Seq count data, and derive an Expectation-Maximization (EM) algorithm to obtain parameter estimates. We also propose a multiple testing procedure that categorizes genes into each of the three states, hypo-tolerant, tolerant, and hyper-tolerant, while controlling false discovery rate. Simulation studies show our method provides good estimation of model parameters and inference on gene functions. In the second project, we model the count data from RNA-sequencing experiment for each gene using a Poisson-Gamma hierarchical model, or equivalently, a negative binomial (NB) model. We derive a full semi-parametric Bayesian approach with Dirichlet process as the prior for the fold changes between two treatment means. An inference strategy using Gibbs algorithm is developed for differential expression analysis. We evaluate our method with several simulation studies, and the results demonstrate that our method outperforms other methods including the popularly applied ones such as edge

  7. Multi-Campus Studies of College Impact: Which Statistical Method Is Appropriate?

    ERIC Educational Resources Information Center

    Astin, Alexander W.; Denson, Nida

    2009-01-01

    In most multi-campus studies of college impact that have been conducted over the past four decades, investigators have relied on ordinary least squares (OLS) regression as the analytic method of choice. Recently, however, some investigators have advocated the use of Hierarchical Linear Modeling (HLM), a method specifically designed for analyses…

  8. A finite element method for the statistics of non-linear random vibration

    NASA Astrophysics Data System (ADS)

    Langley, R. S.

    1985-07-01

    The transitional probability density function for the random response of a certain class of non-linear system satisfies the Fokker-Planck-Kolmogorov equation. This paper concerns the numerical solution of the stationary form of this equation, yielding the stationary probability density function of response. The weighted residual statement for the problem is integrated by parts to yield the weak form of the equations, which are then solved by the finite element method. The method is applied to a Duffing oscillator and good agreement is found with the exact result, and the method is compared favourably with a Galerkin solution method given by Bhandari and Sherrer [1]. Also, the method is applied to the ship rolling problem and good agreement is found with an approximate analytical result due to Roberts [2].

  9. Development of Flood Forecasting Using Statistical Method in Four River Basins in Terengganu, Malaysia

    NASA Astrophysics Data System (ADS)

    Noor, M. S. F. M.; Sidek, L. M.; Basri, H.; Husni, M. M. M.; Jaafar, A. S.; Kamaluddin, M. H.; Majid, W. H. A. W. A.; Mohammad, A. H.; Osman, S.

    2016-03-01

    One of the critical regions in Malaysia is Terengganu which is located at east coast of Peninsular Malaysia. In Terengganu, flood is experienced regularly because of attributed topography and climate including northeast monsoon. Moreover, rainfall is with high intensity during the November to February in Terengganu as forcing factor to produce of flood. In this study, main objectives are water stage forecasting and deriving the related equations based on least squared method. For this study, it is used two methods which called inclusion of residual (Method A) and non-inclusion residual (Method B) respectively. Result depicts that Method B outperformed to forecast the water stage at selected case studies (Besut, Dungun, Kemaman, Terengganu).

  10. An Efficient and Reliable Statistical Method for Estimating Functional Connectivity in Large Scale Brain Networks Using Partial Correlation

    PubMed Central

    Wang, Yikai; Kang, Jian; Kemmer, Phebe B.; Guo, Ying

    2016-01-01

    Currently, network-oriented analysis of fMRI data has become an important tool for understanding brain organization and brain networks. Among the range of network modeling methods, partial correlation has shown great promises in accurately detecting true brain network connections. However, the application of partial correlation in investigating brain connectivity, especially in large-scale brain networks, has been limited so far due to the technical challenges in its estimation. In this paper, we propose an efficient and reliable statistical method for estimating partial correlation in large-scale brain network modeling. Our method derives partial correlation based on the precision matrix estimated via Constrained L1-minimization Approach (CLIME), which is a recently developed statistical method that is more efficient and demonstrates better performance than the existing methods. To help select an appropriate tuning parameter for sparsity control in the network estimation, we propose a new Dens-based selection method that provides a more informative and flexible tool to allow the users to select the tuning parameter based on the desired sparsity level. Another appealing feature of the Dens-based method is that it is much faster than the existing methods, which provides an important advantage in neuroimaging applications. Simulation studies show that the Dens-based method demonstrates comparable or better performance with respect to the existing methods in network estimation. We applied the proposed partial correlation method to investigate resting state functional connectivity using rs-fMRI data from the Philadelphia Neurodevelopmental Cohort (PNC) study. Our results show that partial correlation analysis removed considerable between-module marginal connections identified by full correlation analysis, suggesting these connections were likely caused by global effects or common connection to other nodes. Based on partial correlation, we find that the most significant

  11. Adaptive and robust statistical methods for processing near-field scanning microwave microscopy images.

    PubMed

    Coakley, K J; Imtiaz, A; Wallis, T M; Weber, J C; Berweger, S; Kabos, P

    2015-03-01

    Near-field scanning microwave microscopy offers great potential to facilitate characterization, development and modeling of materials. By acquiring microwave images at multiple frequencies and amplitudes (along with the other modalities) one can study material and device physics at different lateral and depth scales. Images are typically noisy and contaminated by artifacts that can vary from scan line to scan line and planar-like trends due to sample tilt errors. Here, we level images based on an estimate of a smooth 2-d trend determined with a robust implementation of a local regression method. In this robust approach, features and outliers which are not due to the trend are automatically downweighted. We denoise images with the Adaptive Weights Smoothing method. This method smooths out additive noise while preserving edge-like features in images. We demonstrate the feasibility of our methods on topography images and microwave |S11| images. For one challenging test case, we demonstrate that our method outperforms alternative methods from the scanning probe microscopy data analysis software package Gwyddion. Our methods should be useful for massive image data sets where manual selection of landmarks or image subsets by a user is impractical. PMID:25463325

  12. Estimating Small-area Populations by Age and Sex Using Spatial Interpolation and Statistical Inference Methods

    SciTech Connect

    Qai, Qiang; Rushton, Gerald; Bhaduri, Budhendra L; Bright, Eddie A; Coleman, Phil R

    2006-01-01

    The objective of this research is to compute population estimates by age and sex for small areas whose boundaries are different from those for which the population counts were made. In our approach, population surfaces and age-sex proportion surfaces are separately estimated. Age-sex population estimates for small areas and their confidence intervals are then computed using a binomial model with the two surfaces as inputs. The approach was implemented for Iowa using a 90 m resolution population grid (LandScan USA) and U.S. Census 2000 population. Three spatial interpolation methods, the areal weighting (AW) method, the ordinary kriging (OK) method, and a modification of the pycnophylactic method, were used on Census Tract populations to estimate the age-sex proportion surfaces. To verify the model, age-sex population estimates were computed for paired Block Groups that straddled Census Tracts and therefore were spatially misaligned with them. The pycnophylactic method and the OK method were more accurate than the AW method. The approach is general and can be used to estimate subgroup-count types of variables from information in existing administrative areas for custom-defined areas used as the spatial basis of support in other applications.

  13. Cosmic statistics of statistics

    NASA Astrophysics Data System (ADS)

    Szapudi, István; Colombi, Stéphane; Bernardeau, Francis

    1999-12-01

    The errors on statistics measured in finite galaxy catalogues are exhaustively investigated. The theory of errors on factorial moments by Szapudi & Colombi is applied to cumulants via a series expansion method. All results are subsequently extended to the weakly non-linear regime. Together with previous investigations this yields an analytic theory of the errors for moments and connected moments of counts in cells from highly non-linear to weakly non-linear scales. For non-linear functions of unbiased estimators, such as the cumulants, the phenomenon of cosmic bias is identified and computed. Since it is subdued by the cosmic errors in the range of applicability of the theory, correction for it is inconsequential. In addition, the method of Colombi, Szapudi & Szalay concerning sampling effects is generalized, adapting the theory for inhomogeneous galaxy catalogues. While previous work focused on the variance only, the present article calculates the cross-correlations between moments and connected moments as well for a statistically complete description. The final analytic formulae representing the full theory are explicit but somewhat complicated. Therefore we have made available a fortran program capable of calculating the described quantities numerically (for further details e-mail SC at colombi@iap.fr). An important special case is the evaluation of the errors on the two-point correlation function, for which this should be more accurate than any method put forward previously. This tool will be immensely useful in the future for assessing the precision of measurements from existing catalogues, as well as aiding the design of new galaxy surveys. To illustrate the applicability of the results and to explore the numerical aspects of the theory qualitatively and quantitatively, the errors and cross-correlations are predicted under a wide range of assumptions for the future Sloan Digital Sky Survey. The principal results concerning the cumulants ξ, Q3 and Q4 is that

  14. Statistical methods for model discrimination. Applications to gating kinetics and permeation of the acetylcholine receptor channel.

    PubMed Central

    Horn, R

    1987-01-01

    Methods are described for discrimination of models of the gating kinetics and permeation of single ionic channels. Both maximum likelihood and regression procedures are discussed. In simple situations, where models are nested, standard hypothesis tests can be used. More commonly, however, non-nested models are of interest, and several procedures are described for model discrimination in these cases, including Monte Carlo methods, which allow the comparison of models at significance levels of choice. As an illustration, the methods are applied to single-channel data from acetylcholine receptor channels. PMID:2435330

  15. Radiative heat transfer inside a cylindrical enclosure with nonparticipating media using a deterministic statistical method

    SciTech Connect

    Sivathanu, Y.R.; Gore, J.P.

    1996-12-31

    The radiative heat transfer inside a cylindrical enclosure is modeled using a discrete probability function method. The discrete probability function method involves solution of the equation of radiative heat transfer using Lagrangian simulations of representative photon trajectories on a discrete spatial grid. The DPF method is applied to radiation exchange in a cylindrical tube which has a hot source at one end and a detector at the other end. The cylindrical wall absorbs and reflects (both diffusely and specularly) the radiation incident on it. The calculations are used to simulate the effect of collimating tubes used in intrusive multi-wavelength emission spectroscopy. Results highlight the effect of surface properties on the apparent source temperature determined by the detector. The calculation procedure has application to the measurements of spectral absorption and reflection coefficient of the cylindrical surface using an inverse method.

  16. Concatenation and Species Tree Methods Exhibit Statistically Indistinguishable Accuracy under a Range of Simulated Conditions

    PubMed Central

    Tonini, João; Moore, Andrew; Stern, David; Shcheglovitova, Maryia; Ortí, Guillermo

    2015-01-01

    Phylogeneticists have long understood that several biological processes can cause a gene tree to disagree with its species tree. In recent years, molecular phylogeneticists have increasingly foregone traditional supermatrix approaches in favor of species tree methods that account for one such source of error, incomplete lineage sorting (ILS). While gene tree-species tree discordance no doubt poses a significant challenge to phylogenetic inference with molecular data, researchers have only recently begun to systematically evaluate the relative accuracy of traditional and ILS-sensitive methods. Here, we report on simulations demonstrating that concatenation can perform as well or better than methods that attempt to account for sources of error introduced by ILS. Based on these and similar results from other researchers, we argue that concatenation remains a useful component of the phylogeneticist’s toolbox and highlight that phylogeneticists should continue to make explicit comparisons of results produced by contemporaneous and classical methods. PMID:25901289

  17. Statistical inference methods for recurrent event processes with shape and size parameters

    PubMed Central

    WANG, MEI-CHENG; HUANG, CHIUNG-YU

    2015-01-01

    Summary This paper proposes a unified framework to characterize the rate function of a recurrent event process through shape and size parameters. In contrast to the intensity function, which is the event occurrence rate conditional on the event history, the rate function is the occurrence rate unconditional on the event history, and thus it can be interpreted as a population-averaged count of events in unit time. In this paper, shape and size parameters are introduced and used to characterize the association between the rate function λ(·) and a random variable X. Measures of association between X and λ(·) are defined via shape- and size-based coefficients. Rate-independence of X and λ(·) is studied through tests of shape-independence and size-independence, where the shape-and size-based test statistics can be used separately or in combination. These tests can be applied when X is a covariable possibly correlated with the recurrent event process through λ(·) or, in the one-sample setting, when X is the censoring time at which the observation of N(·) is terminated. The proposed tests are shape- and size-based, so when a null hypothesis is rejected, the test results can serve to distinguish the source of violation. PMID:26412863

  18. Statistical methods to study soil infiltration rate in Kharga Oasis, Egypt.

    NASA Astrophysics Data System (ADS)

    Gamie, Rasha; De Smedt, Florimond

    2016-04-01

    Agricultural expansion in the Kahrga oasis, located in the western desert of Egypt, strongly depends on irrigation. Hence, the infiltration rate is a key parameter for further development. The infiltration rate was measured in the field using a double ring infiltrometer at 20 m intervals in a 120 m by 120 m plot, together with 12 other relevant physical and chemical soil parameters. The resulting data were statistically analyzed using principal component and linear regression analyses. Results show that the infiltration rate is highly variable in the study area, and strongly positively correlated with hydraulic conductivity and negatively with silt, clay and carbonates contents of the soil. Principle component analysis showed that most of the variation in the data is assigned in the first 3 principle components. The first component explains 36% of the total variation and is strongly linked with soil structure; the second component explains 18% of the total variation and is linked to soil texture; the third component explains 13% and is linked to chemical properties but has no link with infiltration rate; all other components just represent noise in the data and must be attributed to measurement errors, randomness and soil heterogeneity. Multiple linear regression analysis shows that the only relevant factors to predict infiltration rate are hydraulic conductivity, and silt and carbonate content of the soil. The regression equation is only able to predict about half of the variation of the infiltrations rate, while the other half remains unexplained.

  19. Statistical Methods for Quality Control of Steel Coils Manufacturing Process using Generalized Linear Models

    NASA Astrophysics Data System (ADS)

    García-Díaz, J. Carlos

    2009-11-01

    Fault detection and diagnosis is an important problem in process engineering. Process equipments are subject to malfunctions during operation. Galvanized steel is a value added product, furnishing effective performance by combining the corrosion resistance of zinc with the strength and formability of steel. Fault detection and diagnosis is an important problem in continuous hot dip galvanizing and the increasingly stringent quality requirements in automotive industry has also demanded ongoing efforts in process control to make the process more robust. When faults occur, they change the relationship among these observed variables. This work compares different statistical regression models proposed in the literature for estimating the quality of galvanized steel coils on the basis of short time histories. Data for 26 batches were available. Five variables were selected for monitoring the process: the steel strip velocity, four bath temperatures and bath level. The entire data consisting of 48 galvanized steel coils was divided into sets. The first training data set was 25 conforming coils and the second data set was 23 nonconforming coils. Logistic regression is a modeling tool in which the dependent variable is categorical. In most applications, the dependent variable is binary. The results show that the logistic generalized linear models do provide good estimates of quality coils and can be useful for quality control in manufacturing process.

  20. A statistical method for predicting seizure onset zones from human single-neuron recordings

    NASA Astrophysics Data System (ADS)

    Valdez, André B.; Hickman, Erin N.; Treiman, David M.; Smith, Kris A.; Steinmetz, Peter N.

    2013-02-01

    Objective. Clinicians often use depth-electrode recordings to localize human epileptogenic foci. To advance the diagnostic value of these recordings, we applied logistic regression models to single-neuron recordings from depth-electrode microwires to predict seizure onset zones (SOZs). Approach. We collected data from 17 epilepsy patients at the Barrow Neurological Institute and developed logistic regression models to calculate the odds of observing SOZs in the hippocampus, amygdala and ventromedial prefrontal cortex, based on statistics such as the burst interspike interval (ISI). Main results. Analysis of these models showed that, for a single-unit increase in burst ISI ratio, the left hippocampus was approximately 12 times more likely to contain a SOZ; and the right amygdala, 14.5 times more likely. Our models were most accurate for the hippocampus bilaterally (at 85% average sensitivity), and performance was comparable with current diagnostics such as electroencephalography. Significance. Logistic regression models can be combined with single-neuron recording to predict likely SOZs in epilepsy patients being evaluated for resective surgery, providing an automated source of clinically useful information.