UROX 2.0: an interactive tool for fitting atomic models into electron-microscopy reconstructions
Siebert, Xavier; Navaza, Jorge
2009-01-01
Electron microscopy of a macromolecular structure can lead to three-dimensional reconstructions with resolutions that are typically in the 30–10 Å range and sometimes even beyond 10 Å. Fitting atomic models of the individual components of the macromolecular structure (e.g. those obtained by X-ray crystallography or nuclear magnetic resonance) into an electron-microscopy map allows the interpretation of the latter at near-atomic resolution, providing insight into the interactions between the components. Graphical software is presented that was designed for the interactive fitting and refinement of atomic models into electron-microscopy reconstructions. Several characteristics enable it to be applied over a wide range of cases and resolutions. Firstly, calculations are performed in reciprocal space, which results in fast algorithms. This allows the entire reconstruction (or at least a sizeable portion of it) to be used by taking into account the symmetry of the reconstruction both in the calculations and in the graphical display. Secondly, atomic models can be placed graphically in the map while the correlation between the model-based electron density and the electron-microscopy reconstruction is computed and displayed in real time. The positions and orientations of the models are refined by a least-squares minimization. Thirdly, normal-mode calculations can be used to simulate conformational changes between the atomic model of an individual component and its corresponding density within a macromolecular complex determined by electron microscopy. These features are illustrated using three practical cases with different symmetries and resolutions. The software, together with examples and user instructions, is available free of charge at http://mem.ibs.fr/UROX/. PMID:19564685
Joseph, Agnel P; Swapna, Lakshmipuram S; Rakesh, Ramachandran; Srinivasan, Narayanaswamy
2016-09-01
Protein-protein interface residues, especially those at the core of the interface, exhibit higher conservation than residues in solvent exposed regions. Here, we explore the ability of this differential conservation to evaluate fittings of atomic models in low-resolution cryo-EM maps and select models from the ensemble of solutions that are often proposed by different model fitting techniques. As a prelude, using a non-redundant and high-resolution structural dataset involving 125 permanent and 95 transient complexes, we confirm that core interface residues are conserved significantly better than nearby non-interface residues and this result is used in the cryo-EM map analysis. From the analysis of inter-component interfaces in a set of fitted models associated with low-resolution cryo-EM maps of ribosomes, chaperones and proteasomes we note that a few poorly conserved residues occur at interfaces. Interestingly a few conserved residues are not in the interface, though they are close to the interface. These observations raise the potential requirement of refitting the models in the cryo-EM maps. We show that sampling an ensemble of models and selection of models with high residue conservation at the interface and in good agreement with the density helps in improving the accuracy of the fit. This study indicates that evolutionary information can serve as an additional input to improve and validate fitting of atomic models in cryo-EM density maps. PMID:27444391
NASA Astrophysics Data System (ADS)
Ferreras, Ignacio
2012-08-01
Extracting star formation histories from spectra is a process plagued by numerous degeneracies among the parameters that contribute to the definition of the underlying stellar populations. Traditional approaches to overcome such degeneracies involve carefully defined line strength or spectral fitting procedures. However, all these methods rely on comparisons with population synthesis models. This paper illustrates alternative approaches based on the statistical properties of the information that can be extracted from uniformly selected samples of observed spectra, without any prior reference to modelling. Such methods are more useful with large datasets, such as surveys, where the information from thousands of spectra can be exploited to classify galaxies. An illustrative example is presented on the classification of early-type galaxies with optical spectra from the Sloan Digital Sky Survey.
Fitting PAC spectra with stochastic models: PolyPacFit
NASA Astrophysics Data System (ADS)
Zacate, M. O.; Evenson, W. E.; Newhouse, R.; Collins, G. S.
2010-04-01
PolyPacFit is an advanced fitting program for time-differential perturbed angular correlation (PAC) spectroscopy. It incorporates stochastic models and provides robust options for customization of fits. Notable features of the program include platform independence and support for (1) fits to stochastic models of hyperfine interactions, (2) user-defined constraints among model parameters, (3) fits to multiple spectra simultaneously, and (4) any spin nuclear probe.
ERIC Educational Resources Information Center
Willden, Jeff
2001-01-01
"Bohr's Atomic Model" is a small interactive multimedia program that introduces the viewer to a simplified model of the atom. This interactive simulation lets students build an atom using an atomic construction set. The underlying design methodology for "Bohr's Atomic Model" is model-centered instruction, which means the central model of the…
Fitting and interpreting occupancy models.
Welsh, Alan H; Lindenmayer, David B; Donnelly, Christine F
2013-01-01
We show that occupancy models are more difficult to fit than is generally appreciated because the estimating equations often have multiple solutions, including boundary estimates which produce fitted probabilities of zero or one. The estimates are unstable when the data are sparse, making them difficult to interpret, and, even in ideal situations, highly variable. As a consequence, making accurate inference is difficult. When abundance varies over sites (which is the general rule in ecology because we expect spatial variance in abundance) and detection depends on abundance, the standard analysis suffers bias (attenuation in detection, biased estimates of occupancy and potentially finding misleading relationships between occupancy and other covariates), asymmetric sampling distributions, and slow convergence of the sampling distributions to normality. The key result of this paper is that the biases are of similar magnitude to those obtained when we ignore non-detection entirely. The fact that abundance is subject to detection error and hence is not directly observable, means that we cannot tell when bias is present (or, equivalently, how large it is) and we cannot adjust for it. This implies that we cannot tell which fit is better: the fit from the occupancy model or the fit ignoring the possibility of detection error. Therefore trying to adjust occupancy models for non-detection can be as misleading as ignoring non-detection completely. Ignoring non-detection can actually be better than trying to adjust for it. PMID:23326323
Total force fitness: the military family fitness model.
Bowles, Stephen V; Pollock, Liz Davenport; Moore, Monique; Wadsworth, Shelley MacDermid; Cato, Colanda; Dekle, Judith Ward; Meyer, Sonia Wei; Shriver, Amber; Mueller, Bill; Stephens, Mark; Seidler, Dustin A; Sheldon, Joseph; Picano, James; Finch, Wanda; Morales, Ricardo; Blochberger, Sean; Kleiman, Matthew E; Thompson, Daniel; Bates, Mark J
2015-03-01
The military lifestyle can create formidable challenges for military families. This article describes the Military Family Fitness Model (MFFM), a comprehensive model aimed at enhancing family fitness and resilience across the life span. This model is intended for use by Service members, their families, leaders, and health care providers but also has broader applications for all families. The MFFM has three core components: (1) family demands, (2) resources (including individual resources, family resources, and external resources), and (3) family outcomes (including related metrics). The MFFM proposes that resources from the individual, family, and external areas promote fitness, bolster resilience, and foster well-being for the family. The MFFM highlights each resource level for the purpose of improving family fitness and resilience over time. The MFFM both builds on existing family strengths and encourages the development of new family strengths through resource-acquiring behaviors. The purpose of this article is to (1) expand the military's Total Force Fitness (TFF) intent as it relates to families and (2) offer a family fitness model. This article will summarize relevant evidence, provide supportive theory, describe the model, and proffer metrics that support the dimensions of this model. PMID:25735013
Measured, modeled, and causal conceptions of fitness
Abrams, Marshall
2012-01-01
This paper proposes partial answers to the following questions: in what senses can fitness differences plausibly be considered causes of evolution?What relationships are there between fitness concepts used in empirical research, modeling, and abstract theoretical proposals? How does the relevance of different fitness concepts depend on research questions and methodological constraints? The paper develops a novel taxonomy of fitness concepts, beginning with type fitness (a property of a genotype or phenotype), token fitness (a property of a particular individual), and purely mathematical fitness. Type fitness includes statistical type fitness, which can be measured from population data, and parametric type fitness, which is an underlying property estimated by statistical type fitnesses. Token fitness includes measurable token fitness, which can be measured on an individual, and tendential token fitness, which is assumed to be an underlying property of the individual in its environmental circumstances. Some of the paper's conclusions can be outlined as follows: claims that fitness differences do not cause evolution are reasonable when fitness is treated as statistical type fitness, measurable token fitness, or purely mathematical fitness. Some of the ways in which statistical methods are used in population genetics suggest that what natural selection involves are differences in parametric type fitnesses. Further, it's reasonable to think that differences in parametric type fitness can cause evolution. Tendential token fitnesses, however, are not themselves sufficient for natural selection. Though parametric type fitnesses are typically not directly measurable, they can be modeled with purely mathematical fitnesses and estimated by statistical type fitnesses, which in turn are defined in terms of measurable token fitnesses. The paper clarifies the ways in which fitnesses depend on pragmatic choices made by researchers. PMID:23112804
Coaches as Fitness Role Models
ERIC Educational Resources Information Center
Nichols, Randall; Zillifro, Traci D.; Nichols, Ronald; Hull, Ethan E.
2012-01-01
The lack of physical activity, low fitness levels, and elevated obesity rates as high as 32% of today's youth are well documented. Many strategies and grants have been developed at the national, regional, and local levels to help counteract these current trends. Strategies have been developed and implemented for schools, households (parents), and…
Sensitivity of Fit Indices to Model Misspecification and Model Types
ERIC Educational Resources Information Center
Fan, Xitao; Sivo, Stephen A.
2007-01-01
The search for cut-off criteria of fit indices for model fit evaluation (e.g., Hu & Bentler, 1999) assumes that these fit indices are sensitive to model misspecification, but not to different types of models. If fit indices were sensitive to different types of models that are misspecified to the same degree, it would be very difficult to establish…
Computer Modeling Of Atomization
NASA Technical Reports Server (NTRS)
Giridharan, M.; Ibrahim, E.; Przekwas, A.; Cheuch, S.; Krishnan, A.; Yang, H.; Lee, J.
1994-01-01
Improved mathematical models based on fundamental principles of conservation of mass, energy, and momentum developed for use in computer simulation of atomization of jets of liquid fuel in rocket engines. Models also used to study atomization in terrestrial applications; prove especially useful in designing improved industrial sprays - humidifier water sprays, chemical process sprays, and sprays of molten metal. Because present improved mathematical models based on first principles, they are minimally dependent on empirical correlations and better able to represent hot-flow conditions that prevail in rocket engines and are too severe to be accessible for detailed experimentation.
Evaluation of Model Fit in Cognitive Diagnosis Models
ERIC Educational Resources Information Center
Hu, Jinxiang; Miller, M. David; Huggins-Manley, Anne Corinne; Chen, Yi-Hsin
2016-01-01
Cognitive diagnosis models (CDMs) estimate student ability profiles using latent attributes. Model fit to the data needs to be ascertained in order to determine whether inferences from CDMs are valid. This study investigated the usefulness of some popular model fit statistics to detect CDM fit including relative fit indices (AIC, BIC, and CAIC),…
Evaluating Model Fit for Growth Curve Models: Integration of Fit Indices from SEM and MLM Frameworks
ERIC Educational Resources Information Center
Wu, Wei; West, Stephen G.; Taylor, Aaron B.
2009-01-01
Evaluating overall model fit for growth curve models involves 3 challenging issues. (a) Three types of longitudinal data with different implications for model fit may be distinguished: balanced on time with complete data, balanced on time with data missing at random, and unbalanced on time. (b) Traditional work on fit from the structural equation…
Are Physical Education Majors Models for Fitness?
ERIC Educational Resources Information Center
Kamla, James; Snyder, Ben; Tanner, Lori; Wash, Pamela
2012-01-01
The National Association of Sport and Physical Education (NASPE) (2002) has taken a firm stance on the importance of adequate fitness levels of physical education teachers stating that they have the responsibility to model an active lifestyle and to promote fitness behaviors. Since the NASPE declaration, national initiatives like Let's Move…
Fitting Neuron Models to Spike Trains
Rossant, Cyrille; Goodman, Dan F. M.; Fontaine, Bertrand; Platkiewicz, Jonathan; Magnusson, Anna K.; Brette, Romain
2011-01-01
Computational modeling is increasingly used to understand the function of neural circuits in systems neuroscience. These studies require models of individual neurons with realistic input–output properties. Recently, it was found that spiking models can accurately predict the precisely timed spike trains produced by cortical neurons in response to somatically injected currents, if properly fitted. This requires fitting techniques that are efficient and flexible enough to easily test different candidate models. We present a generic solution, based on the Brian simulator (a neural network simulator in Python), which allows the user to define and fit arbitrary neuron models to electrophysiological recordings. It relies on vectorization and parallel computing techniques to achieve efficiency. We demonstrate its use on neural recordings in the barrel cortex and in the auditory brainstem, and confirm that simple adaptive spiking models can accurately predict the response of cortical neurons. Finally, we show how a complex multicompartmental model can be reduced to a simple effective spiking model. PMID:21415925
Pearson, Ralph G.
1981-01-01
The energies of several two- and three-electron atoms, in both ground states and excited states, are calculated by a very simple semiclassical model. The only change from Bohr's original method is to replace definite orbits by probability distribution functions based on classical dynamics. The energies are better than Hartree-Fock values. There is still a need for an exchange-energy correction. Images PMID:16593047
Students' Models of Curve Fitting: A Models and Modeling Perspective
ERIC Educational Resources Information Center
Gupta, Shweta
2010-01-01
The Models and Modeling Perspectives (MMP) has evolved out of research that began 26 years ago. MMP researchers use Model Eliciting Activities (MEAs) to elicit students' mental models. In this study MMP was used as the conceptual framework to investigate the nature of students' models of curve fitting in a problem-solving environment consisting of…
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Hollman, David S; Schaefer, Henry F; Valeev, Edward F
2014-02-14
A local density fitting scheme is considered in which atomic orbital (AO) products are approximated using only auxiliary AOs located on one of the nuclei in that product. The possibility of variational collapse to an unphysical "attractive electron" state that can affect such density fitting [P. Merlot, T. Kjærgaard, T. Helgaker, R. Lindh, F. Aquilante, S. Reine, and T. B. Pedersen, J. Comput. Chem. 34, 1486 (2013)] is alleviated by including atom-wise semidiagonal integrals exactly. Our approach leads to a significant decrease in the computational cost of density fitting for Hartree-Fock theory while still producing results with errors 2-5 times smaller than standard, nonlocal density fitting. Our method allows for large Hartree-Fock and density functional theory computations with exact exchange to be carried out efficiently on large molecules, which we demonstrate by benchmarking our method on 200 of the most widely used prescription drug molecules. Our new fitting scheme leads to smooth and artifact-free potential energy surfaces and the possibility of relatively simple analytic gradients. PMID:24527902
A predictive fitness model for influenza
NASA Astrophysics Data System (ADS)
Łuksza, Marta; Lässig, Michael
2014-03-01
The seasonal human influenza A/H3N2 virus undergoes rapid evolution, which produces significant year-to-year sequence turnover in the population of circulating strains. Adaptive mutations respond to human immune challenge and occur primarily in antigenic epitopes, the antibody-binding domains of the viral surface protein haemagglutinin. Here we develop a fitness model for haemagglutinin that predicts the evolution of the viral population from one year to the next. Two factors are shown to determine the fitness of a strain: adaptive epitope changes and deleterious mutations outside the epitopes. We infer both fitness components for the strains circulating in a given year, using population-genetic data of all previous strains. From fitness and frequency of each strain, we predict the frequency of its descendent strains in the following year. This fitness model maps the adaptive history of influenza A and suggests a principled method for vaccine selection. Our results call for a more comprehensive epidemiology of influenza and other fast-evolving pathogens that integrates antigenic phenotypes with other viral functions coupled by genetic linkage.
Modeling and Fitting Exoplanet Transit Light Curves
NASA Astrophysics Data System (ADS)
Millholland, Sarah; Ruch, G. T.
2013-01-01
We present a numerical model along with an original fitting routine for the analysis of transiting extra-solar planet light curves. Our light curve model is unique in several ways from other available transit models, such as the analytic eclipse formulae of Mandel & Agol (2002) and Giménez (2006), the modified Eclipsing Binary Orbit Program (EBOP) model implemented in Southworth’s JKTEBOP code (Popper & Etzel 1981; Southworth et al. 2004), or the transit model developed as a part of the EXOFAST fitting suite (Eastman et al. in prep.). Our model employs Keplerian orbital dynamics about the system’s center of mass to properly account for stellar wobble and orbital eccentricity, uses a unique analytic solution derived from Kepler’s Second Law to calculate the projected distance between the centers of the star and planet, and calculates the effect of limb darkening using a simple technique that is different from the commonly used eclipse formulae. We have also devised a unique Monte Carlo style optimization routine for fitting the light curve model to observed transits. We demonstrate that, while the effect of stellar wobble on transit light curves is generally small, it becomes significant as the planet to stellar mass ratio increases and the semi-major axes of the orbits decrease. We also illustrate the appreciable effects of orbital ellipticity on the light curve and the necessity of accounting for its impacts for accurate modeling. We show that our simple limb darkening calculations are as accurate as the analytic equations of Mandel & Agol (2002). Although our Monte Carlo fitting algorithm is not as mathematically rigorous as the Markov Chain Monte Carlo based algorithms most often used to determine exoplanetary system parameters, we show that it is straightforward and returns reliable results. Finally, we show that analyses performed with our model and optimization routine compare favorably with exoplanet characterizations published by groups such as the
Degeneracy and discreteness in cosmological model fitting
NASA Astrophysics Data System (ADS)
Teng, Huan-Yu; Huang, Yuan; Zhang, Tong-Jie
2016-03-01
We explore the problems of degeneracy and discreteness in the standard cosmological model (ΛCDM). We use the Observational Hubble Data (OHD) and the type Ia supernovae (SNe Ia) data to study this issue. In order to describe the discreteness in fitting of data, we define a factor G to test the influence from each single data point and analyze the goodness of G. Our results indicate that a higher absolute value of G shows a better capability of distinguishing models, which means the parameters are restricted into smaller confidence intervals with a larger figure of merit evaluation. Consequently, we claim that the factor G is an effective way of model differentiation when using different models to fit the observational data.
Model Fit after Pairwise Maximum Likelihood
Barendse, M. T.; Ligtvoet, R.; Timmerman, M. E.; Oort, F. J.
2016-01-01
Maximum likelihood factor analysis of discrete data within the structural equation modeling framework rests on the assumption that the observed discrete responses are manifestations of underlying continuous scores that are normally distributed. As maximizing the likelihood of multivariate response patterns is computationally very intensive, the sum of the log–likelihoods of the bivariate response patterns is maximized instead. Little is yet known about how to assess model fit when the analysis is based on such a pairwise maximum likelihood (PML) of two–way contingency tables. We propose new fit criteria for the PML method and conduct a simulation study to evaluate their performance in model selection. With large sample sizes (500 or more), PML performs as well the robust weighted least squares analysis of polychoric correlations. PMID:27148136
Model Fit after Pairwise Maximum Likelihood.
Barendse, M T; Ligtvoet, R; Timmerman, M E; Oort, F J
2016-01-01
Maximum likelihood factor analysis of discrete data within the structural equation modeling framework rests on the assumption that the observed discrete responses are manifestations of underlying continuous scores that are normally distributed. As maximizing the likelihood of multivariate response patterns is computationally very intensive, the sum of the log-likelihoods of the bivariate response patterns is maximized instead. Little is yet known about how to assess model fit when the analysis is based on such a pairwise maximum likelihood (PML) of two-way contingency tables. We propose new fit criteria for the PML method and conduct a simulation study to evaluate their performance in model selection. With large sample sizes (500 or more), PML performs as well the robust weighted least squares analysis of polychoric correlations. PMID:27148136
Model-based estimation of individual fitness
Link, W.A.; Cooch, E.G.; Cam, E.
2002-01-01
Fitness is the currency of natural selection, a measure of the propagation rate of genotypes into future generations. Its various definitions have the common feature that they are functions of survival and fertility rates. At the individual level, the operative level for natural selection, these rates must be understood as latent features, genetically determined propensities existing at birth. This conception of rates requires that individual fitness be defined and estimated by consideration of the individual in a modelled relation to a group of similar individuals; the only alternative is to consider a sample of size one, unless a clone of identical individuals is available. We present hierarchical models describing individual heterogeneity in survival and fertility rates and allowing for associations between these rates at the individual level. We apply these models to an analysis of life histories of Kittiwakes (Rissa tridactyla) observed at several colonies on the Brittany coast of France. We compare Bayesian estimation of the population distribution of individual fitness with estimation based on treating individual life histories in isolation, as samples of size one (e.g. McGraw and Caswell, 1996).
Model-based estimation of individual fitness
Link, W.A.; Cooch, E.G.; Cam, E.
2002-01-01
Fitness is the currency of natural selection, a measure of the propagation rate of genotypes into future generations. Its various definitions have the common feature that they are functions of survival and fertility rates. At the individual level, the operative level for natural selection, these rates must be understood as latent features, genetically determined propensities existing at birth. This conception of rates requires that individual fitness be defined and estimated by consideration of the individual in a modelled relation to a group of similar individuals; the only alternative is to consider a sample of size one, unless a clone of identical individuals is available. We present hierarchical models describing individual heterogeneity in survival and fertility rates and allowing for associations between these rates at the individual level. We apply these models to an analysis of life histories of Kittiwakes (Rissa tridactyla ) observed at several colonies on the Brittany coast of France. We compare Bayesian estimation of the population distribution of individual fitness with estimation based on treating individual life histories in isolation, as samples of size one (e.g. McGraw & Caswell, 1996).
ERIC Educational Resources Information Center
Hayduk, Leslie
2014-01-01
Researchers using factor analysis tend to dismiss the significant ill fit of factor models by presuming that if their factor model is close-to-fitting, it is probably close to being properly causally specified. Close fit may indeed result from a model being close to properly causally specified, but close-fitting factor models can also be seriously…
An Investigation of Goodness of Model Data Fit
ERIC Educational Resources Information Center
Onder, Ismail
2007-01-01
IRT models' advantages can only be realized when the model fits the data set of interest. Therefore, this study aimed to investigate which IRT model will provide the best fit to the data obtained from OZDEBYR OSS 2004 D-II Exam Science Test. In goodness-of-fit analysis, first the model assumptions and then the expected model features were checked.…
An Investigation of Item Fit Statistics for Mixed IRT Models
ERIC Educational Resources Information Center
Chon, Kyong Hee
2009-01-01
The purpose of this study was to investigate procedures for assessing model fit of IRT models for mixed format data. In this study, various IRT model combinations were fitted to data containing both dichotomous and polytomous item responses, and the suitability of the chosen model mixtures was evaluated based on a number of model fit procedures.…
Fitting and Modeling of AXAF Data with the ASC Fitting Application
NASA Astrophysics Data System (ADS)
Doe, S.; Ljungberg, M.; Siemiginowska, A.; Joye, W.
The AXAF mission will provide X-ray data with unprecedented spatial and spectral resolution. Because of the high quality of these data, the AXAF Science Center will provide a new data analysis system--including a new fitting application. Our intent is to enable users to do fitting that is too awkward with, or beyond, the scope of existing astronomical fitting software. Our main goals are: 1) to take advantage of the full capabilities of the AXAF, we intend to provide a more sophisticated modeling capability (i.e., models that are $f(x,y,E,t)$, models to simulate the response of AXAF instruments, and models that enable ``joint-mode'' fitting, i.e., combined spatial-spectral or spectral-temporal fitting); and 2) to provide users with a wide variety of models, optimization methods, and fit statistics. In this paper, we discuss the use of an object-oriented approach in our implementation, the current features of the fitting application, and the features scheduled to be added in the coming year of development. Current features include: an interactive, command-line interface; a modeling language, which allows users to build models from arithmetic combinations of base functions; a suite of optimization and fit statistics; the ability to perform fits to multiple data sets simultaneously; and, an interface with SM and SAOtng to plot or image data, models, and/or residuals from a fit. We currently provide a modeling capability in one or two dimensions, and have recently made an effort to perform spectral fitting in a manner similar to XSPEC. We also allow users to dynamically link the fitting application to their own algorithms. Our goals for the coming year include incorporating the XSPEC model library as a subset of models available in the application, enabling ``joint-mode'' analysis and adding support for new algorithms.
Evaluating Latent Growth Curve Models Using Individual Fit Statistics
ERIC Educational Resources Information Center
Coffman, Donna L.; Millsap, Roger E.
2006-01-01
The usefulness of assessing individual fit in latent growth curve models was examined. The study used simulated data based on an unconditional and a conditional latent growth curve model with a linear component and a small quadratic component and a linear model was fit to the data. Then the overall fit of linear and quadratic models to these data…
Goodness-of-Fit Assessment of Item Response Theory Models
ERIC Educational Resources Information Center
Maydeu-Olivares, Alberto
2013-01-01
The article provides an overview of goodness-of-fit assessment methods for item response theory (IRT) models. It is now possible to obtain accurate "p"-values of the overall fit of the model if bivariate information statistics are used. Several alternative approaches are described. As the validity of inferences drawn on the fitted model…
Stochastic models for atomic clocks
NASA Technical Reports Server (NTRS)
Barnes, J. A.; Jones, R. H.; Tryon, P. V.; Allan, D. W.
1983-01-01
For the atomic clocks used in the National Bureau of Standards Time Scales, an adequate model is the superposition of white FM, random walk FM, and linear frequency drift for times longer than about one minute. The model was tested on several clocks using maximum likelihood techniques for parameter estimation and the residuals were acceptably random. Conventional diagnostics indicate that additional model elements contribute no significant improvement to the model even at the expense of the added model complexity.
Blanquart, François; Bataillon, Thomas
2016-06-01
The fitness landscape defines the relationship between genotypes and fitness in a given environment and underlies fundamental quantities such as the distribution of selection coefficient and the magnitude and type of epistasis. A better understanding of variation in landscape structure across species and environments is thus necessary to understand and predict how populations will adapt. An increasing number of experiments investigate the properties of fitness landscapes by identifying mutations, constructing genotypes with combinations of these mutations, and measuring the fitness of these genotypes. Yet these empirical landscapes represent a very small sample of the vast space of all possible genotypes, and this sample is often biased by the protocol used to identify mutations. Here we develop a rigorous statistical framework based on Approximate Bayesian Computation to address these concerns and use this flexible framework to fit a broad class of phenotypic fitness models (including Fisher's model) to 26 empirical landscapes representing nine diverse biological systems. Despite uncertainty owing to the small size of most published empirical landscapes, the inferred landscapes have similar structure in similar biological systems. Surprisingly, goodness-of-fit tests reveal that this class of phenotypic models, which has been successful so far in interpreting experimental data, is a plausible in only three of nine biological systems. More precisely, although Fisher's model was able to explain several statistical properties of the landscapes-including the mean and SD of selection and epistasis coefficients-it was often unable to explain the full structure of fitness landscapes. PMID:27052568
ERIC Educational Resources Information Center
Pritchard, Tony; Hansen, Andrew; Scarboro, Shot; Melnic, Irina
2015-01-01
The purpose of this study was to investigate changes in fitness levels, content knowledge, physical activity levels, and participants' perceptions following the implementation of the sport education fitness model (SEFM) at a high school. Thirty-two high school students participated in 20 lessons using the SEFM. Aerobic capacity, muscular…
Hyper-Fit: Fitting Linear Models to Multidimensional Data with Multivariate Gaussian Uncertainties
NASA Astrophysics Data System (ADS)
Robotham, A. S. G.; Obreschkow, D.
2015-09-01
Astronomical data is often uncertain with errors that are heteroscedastic (different for each data point) and covariant between different dimensions. Assuming that a set of D-dimensional data points can be described by a (D - 1)-dimensional plane with intrinsic scatter, we derive the general likelihood function to be maximised to recover the best fitting model. Alongside the mathematical description, we also release the hyper-fit package for the R statistical language (http://github.com/asgr/hyper.fit) and a user-friendly web interface for online fitting (http://hyperfit.icrar.org). The hyper-fit package offers access to a large number of fitting routines, includes visualisation tools, and is fully documented in an extensive user manual. Most of the hyper-fit functionality is accessible via the web interface. In this paper, we include applications to toy examples and to real astronomical data from the literature: the mass-size, Tully-Fisher, Fundamental Plane, and mass-spin-morphology relations. In most cases, the hyper-fit solutions are in good agreement with published values, but uncover more information regarding the fitted model.
Curve fitting methods for solar radiation data modeling
Karim, Samsul Ariffin Abdul E-mail: balbir@petronas.com.my; Singh, Balbir Singh Mahinder E-mail: balbir@petronas.com.my
2014-10-24
This paper studies the use of several type of curve fitting method to smooth the global solar radiation data. After the data have been fitted by using curve fitting method, the mathematical model of global solar radiation will be developed. The error measurement was calculated by using goodness-fit statistics such as root mean square error (RMSE) and the value of R{sup 2}. The best fitting methods will be used as a starting point for the construction of mathematical modeling of solar radiation received in Universiti Teknologi PETRONAS (UTP) Malaysia. Numerical results indicated that Gaussian fitting and sine fitting (both with two terms) gives better results as compare with the other fitting methods.
Curve fitting methods for solar radiation data modeling
NASA Astrophysics Data System (ADS)
Karim, Samsul Ariffin Abdul; Singh, Balbir Singh Mahinder
2014-10-01
This paper studies the use of several type of curve fitting method to smooth the global solar radiation data. After the data have been fitted by using curve fitting method, the mathematical model of global solar radiation will be developed. The error measurement was calculated by using goodness-fit statistics such as root mean square error (RMSE) and the value of R2. The best fitting methods will be used as a starting point for the construction of mathematical modeling of solar radiation received in Universiti Teknologi PETRONAS (UTP) Malaysia. Numerical results indicated that Gaussian fitting and sine fitting (both with two terms) gives better results as compare with the other fitting methods.
Deviance statistics in model fit and selection in ROC studies
NASA Astrophysics Data System (ADS)
Lei, Tianhu; Bae, K. Ty
2013-03-01
A general non-linear regression model-based Bayesian inference approach is used in our ROC (Receiver Operating Characteristics) study. In the sampling of posterior distribution, two prior models - continuous Gaussian and discrete categorical - are used for the scale parameter. How to judge Goodness-of-Fit (GOF) of each model and how to criticize these two models, Deviance statistics and Deviance information criterion (DIC) are adopted to address these problems. Model fit and model selection focus on the adequacy of models. Judging model adequacy is essentially measuring agreement of model and observations. Deviance statistics and DIC provide overall measures on model fit and selection. In order to investigate model fit at each category of observations, we find that the cumulative, exponential contributions from individual observations to Deviance statistics are good estimates of FPF (false positive fraction) and TPF (true positive fraction) on which the ROC curve is based. This finding further leads to a new measure for model fit, called FPF-TPF distance, which is an Euclidean distance defined on FPF-TPF space. It combines both local and global fitting. Deviance statistics and FPFTPF distance are shown to be consistent and in good agreement. Theoretical derivation and numerical simulations for this new method for model fit and model selection of ROC data analysis are included. Keywords: General non-linear regression model, Bayesian Inference, Markov Chain Monte Carlo (MCMC) method, Goodness-of-Fit (GOF), Model selection, Deviance statistics, Deviance information criterion (DIC), Continuous conjugate prior, Discrete categorical prior. ∗
On the Fitting of Non-Linear, Empirical Functions for the Fitting of Model Crater Ages
NASA Astrophysics Data System (ADS)
Weaver, B. P.; Hilbe, J. M.; Robbins, S. J.; Plesko, C. S.; Riggs, J. D.
2015-05-01
Fitting model crater production functions to observed crater data is considered an "art" by many, and there is no standard in the field for how best to do it. We will discuss mathematical techniques' pros and cons and make recommendations.
Two strategies for fitting real data to Rasch polytomous models.
Rojas Tejada, Antonio J; Gonzalez Gomez, Andres; Padilla Garcia, Jose L; Perez Melendez, Cristino
2002-01-01
A comparative study of the results provided by two strategies for fitting data to Latent Trait Theory Models has been performed. The first, called Total-Persons-Items (TPI), is structured in three phases: 1) assessment of item fit, 2) assessment of person fit; and finally, 3) overall fit of data to the models (items and persons). The second strategy, the Total-Items-Persons (TIP), changes the order of the phases: 1) assessment of person fit, 2) assessment of item fit and, 3) overall fit of data to the models. To verify the results of these two strategies, a set of 30 items, designed to measure religious attitude, was administered to a sample of 821 persons. The Latent Trait Theory Models used were the Partial Credit Model and the Rating Scale Model. The results underline an important difference between the two procedures: the TPI maximizes the number of persons with good fit and the TIP maximizes the number of items with good fit. Moreover, a procedure for controlling the sensitivity of fit to sample size is proposed. PMID:12011498
Goodness of Model-Data Fit and Invariant Measurement
ERIC Educational Resources Information Center
Engelhard, George, Jr.; Perkins, Aminah
2013-01-01
In this commentary, Englehard and Perkins remark that Maydeu-Olivares has presented a framework for evaluating the goodness of model-data fit for item response theory (IRT) models and correctly points out that overall goodness-of-fit evaluations of IRT models and data are not generally explored within most applications in educational and…
A Comparison of Item Fit Statistics for Mixed IRT Models
ERIC Educational Resources Information Center
Chon, Kyong Hee; Lee, Won-Chan; Dunbar, Stephen B.
2010-01-01
In this study we examined procedures for assessing model-data fit of item response theory (IRT) models for mixed format data. The model fit indices used in this study include PARSCALE's G[superscript 2], Orlando and Thissen's S-X[superscript 2] and S-G[superscript 2], and Stone's chi[superscript 2*] and G[superscript 2*]. To investigate the…
A Quantum Model of Atoms (the Energy Levels of Atoms).
ERIC Educational Resources Information Center
Rafie, Francois
2001-01-01
Discusses the model for all atoms which was developed on the same basis as Bohr's model for the hydrogen atom. Calculates the radii and the energies of the orbits. Demonstrates how the model obeys the de Broglie's hypothesis that the moving electron exhibits both wave and particle properties. (Author/ASK)
"Electronium": A Quantum Atomic Teaching Model.
ERIC Educational Resources Information Center
Budde, Marion; Niedderer, Hans; Scott, Philip; Leach, John
2002-01-01
Outlines an alternative atomic model to the probability model, the descriptive quantum atomic model Electronium. Discusses the way in which it is intended to support students in learning quantum-mechanical concepts. (Author/MM)
Sensitivity of Fit Indices to Misspecification in Growth Curve Models
ERIC Educational Resources Information Center
Wu, Wei; West, Stephen G.
2010-01-01
This study investigated the sensitivity of fit indices to model misspecification in within-individual covariance structure, between-individual covariance structure, and marginal mean structure in growth curve models. Five commonly used fit indices were examined, including the likelihood ratio test statistic, root mean square error of…
Model-Free CUSUM Methods for Person Fit
ERIC Educational Resources Information Center
Armstrong, Ronald D.; Shi, Min
2009-01-01
This article demonstrates the use of a new class of model-free cumulative sum (CUSUM) statistics to detect person fit given the responses to a linear test. The fundamental statistic being accumulated is the likelihood ratio of two probabilities. The detection performance of this CUSUM scheme is compared to other model-free person-fit statistics…
From electron microscopy maps to atomic structures using normal mode-based fitting.
Hinsen, Konrad; Beaumont, Edward; Fournier, Bertrand; Lacapère, Jean-Jacques
2010-01-01
Electron microscopy (EM) has made possible to solve the structure of many proteins. However, the resolution of some of the EM maps is too low for interpretation at the atomic level, which is particularly important to describe function. We describe methods that combine low-resolution EM data with atomic structures for different conformations of the same protein in order to produce atomic models compatible with the EM map.We illustrate these methods with EM data from decavanadate-induced tubular crystals of a pseudo-phosphorylated intermediate of Ca-ATPase and the various atomic structures of other intermediates available in the Protein Data Bank (PDB). Determination of atomic structure permits not only to analyse protein-protein interactions in the crystals, but also to localize residues in the proximity of the crystallizing agent both within Ca-ATPase and between Ca-ATPase molecules. PMID:20665270
Modeling of atom-diatom scattering. Technical report
Sindoni, J.M.
1992-05-30
This report entails the work performed on modeling atom-diatom scattering processes utilizing the Impulse Approach (IA). Results of the model, obtained with a computer code, have proven to be in remarkable agreement with laboratory measurements for several atom-diatom scattering systems. Two scattering systems, in particular, that were successfully modeled and compared to measurements were Ar-KBr and Ar-CsF. The IA model provided an explanation for the rapid deactivation evident in the Ar-KBr system. Experimental results in the Ar-CsF experiment that could not be explained by conventional models were also successfully modeled using the IA. Results fit the experimental observations.
NASA Astrophysics Data System (ADS)
Li, Jun; Jiang, Bin; Guo, Hua
2013-11-01
A rigorous, general, and simple method to fit global and permutation invariant potential energy surfaces (PESs) using neural networks (NNs) is discussed. This so-called permutation invariant polynomial neural network (PIP-NN) method imposes permutation symmetry by using in its input a set of symmetry functions based on PIPs. For systems with more than three atoms, it is shown that the number of symmetry functions in the input vector needs to be larger than the number of internal coordinates in order to include both the primary and secondary invariant polynomials. This PIP-NN method is successfully demonstrated in three atom-triatomic reactive systems, resulting in full-dimensional global PESs with average errors on the order of meV. These PESs are used in full-dimensional quantum dynamical calculations.
Li, Jun; Jiang, Bin; Guo, Hua
2013-11-28
A rigorous, general, and simple method to fit global and permutation invariant potential energy surfaces (PESs) using neural networks (NNs) is discussed. This so-called permutation invariant polynomial neural network (PIP-NN) method imposes permutation symmetry by using in its input a set of symmetry functions based on PIPs. For systems with more than three atoms, it is shown that the number of symmetry functions in the input vector needs to be larger than the number of internal coordinates in order to include both the primary and secondary invariant polynomials. This PIP-NN method is successfully demonstrated in three atom-triatomic reactive systems, resulting in full-dimensional global PESs with average errors on the order of meV. These PESs are used in full-dimensional quantum dynamical calculations.
HDFITS: Porting the FITS data model to HDF5
NASA Astrophysics Data System (ADS)
Price, D. C.; Barsdell, B. R.; Greenhill, L. J.
2015-09-01
The FITS (Flexible Image Transport System) data format has been the de facto data format for astronomy-related data products since its inception in the late 1970s. While the FITS file format is widely supported, it lacks many of the features of more modern data serialization, such as the Hierarchical Data Format (HDF5). The HDF5 file format offers considerable advantages over FITS, such as improved I/O speed and compression, but has yet to gain widespread adoption within astronomy. One of the major holdbacks is that HDF5 is not well supported by data reduction software packages and image viewers. Here, we present a comparison of FITS and HDF5 as a format for storage of astronomy datasets. We show that the underlying data model of FITS can be ported to HDF5 in a straightforward manner, and that by doing so the advantages of the HDF5 file format can be leveraged immediately. In addition, we present a software tool, fits2hdf, for converting between FITS and a new 'HDFITS' format, where data are stored in HDF5 in a FITS-like manner. We show that HDFITS allows faster reading of data (up to 100x of FITS in some use cases), and improved compression (higher compression ratios and higher throughput). Finally, we show that by only changing the import lines in Python-based FITS utilities, HDFITS formatted data can be presented transparently as an in-memory FITS equivalent.
A liquid drop model for embedded atom method cluster energies
NASA Technical Reports Server (NTRS)
Finley, C. W.; Abel, P. B.; Ferrante, J.
1996-01-01
Minimum energy configurations for homonuclear clusters containing from two to twenty-two atoms of six metals, Ag, Au, Cu, Ni, Pd, and Pt have been calculated using the Embedded Atom Method (EAM). The average energy per atom as a function of cluster size has been fit to a liquid drop model, giving estimates of the surface and curvature energies. The liquid drop model gives a good representation of the relationship between average energy and cluster size. As a test the resulting surface energies are compared to EAM surface energy calculations for various low-index crystal faces with reasonable agreement.
Consequences of Fitting Nonidentified Latent Class Models
ERIC Educational Resources Information Center
Abar, Beau; Loken, Eric
2012-01-01
Latent class models are becoming more popular in behavioral research. When models with a large number of latent classes relative to the number of manifest indicators are estimated, researchers must consider the possibility that the model is not identified. It is not enough to determine that the model has positive degrees of freedom. A well-known…
Fitting Value-Added Models in R
ERIC Educational Resources Information Center
Doran, Harold C.; Lockwood, J. R.
2006-01-01
Value-added models of student achievement have received widespread attention in light of the current test-based accountability movement. These models use longitudinal growth modeling techniques to identify effective schools or teachers based upon the results of changes in student achievement test scores. Given their increasing popularity, this…
Two Strategies for Fitting Real Data to Rasch Polytomous Models.
ERIC Educational Resources Information Center
Rojas Tejada, Antonio J.; Gonzalez Gomez, Andres; Padilla Garcia, Jose L.; Perez Melendez, Cristino
2002-01-01
Studied the results provided by two strategies for fitting data to Latent Trait Theory models, Total-Persons-Items (TPI) and Total-Items-Persons (TIP). To assess these strategies, 30 items measuring religious attitudes were administered to 821 persons. Results show that TPI maximizes the number of persons with good fit, and TIP maximizes the…
Evaluating Item Fit for Multidimensional Item Response Models
ERIC Educational Resources Information Center
Zhang, Bo; Stone, Clement A.
2008-01-01
This research examines the utility of the s-x[superscript 2] statistic proposed by Orlando and Thissen (2000) in evaluating item fit for multidimensional item response models. Monte Carlo simulation was conducted to investigate both the Type I error and statistical power of this fit statistic in analyzing two kinds of multidimensional test…
How Good Are Statistical Models at Approximating Complex Fitness Landscapes?
du Plessis, Louis; Leventhal, Gabriel E.; Bonhoeffer, Sebastian
2016-01-01
Fitness landscapes determine the course of adaptation by constraining and shaping evolutionary trajectories. Knowledge of the structure of a fitness landscape can thus predict evolutionary outcomes. Empirical fitness landscapes, however, have so far only offered limited insight into real-world questions, as the high dimensionality of sequence spaces makes it impossible to exhaustively measure the fitness of all variants of biologically meaningful sequences. We must therefore revert to statistical descriptions of fitness landscapes that are based on a sparse sample of fitness measurements. It remains unclear, however, how much data are required for such statistical descriptions to be useful. Here, we assess the ability of regression models accounting for single and pairwise mutations to correctly approximate a complex quasi-empirical fitness landscape. We compare approximations based on various sampling regimes of an RNA landscape and find that the sampling regime strongly influences the quality of the regression. On the one hand it is generally impossible to generate sufficient samples to achieve a good approximation of the complete fitness landscape, and on the other hand systematic sampling schemes can only provide a good description of the immediate neighborhood of a sequence of interest. Nevertheless, we obtain a remarkably good and unbiased fit to the local landscape when using sequences from a population that has evolved under strong selection. Thus, current statistical methods can provide a good approximation to the landscape of naturally evolving populations. PMID:27189564
How Good Are Statistical Models at Approximating Complex Fitness Landscapes?
du Plessis, Louis; Leventhal, Gabriel E; Bonhoeffer, Sebastian
2016-09-01
Fitness landscapes determine the course of adaptation by constraining and shaping evolutionary trajectories. Knowledge of the structure of a fitness landscape can thus predict evolutionary outcomes. Empirical fitness landscapes, however, have so far only offered limited insight into real-world questions, as the high dimensionality of sequence spaces makes it impossible to exhaustively measure the fitness of all variants of biologically meaningful sequences. We must therefore revert to statistical descriptions of fitness landscapes that are based on a sparse sample of fitness measurements. It remains unclear, however, how much data are required for such statistical descriptions to be useful. Here, we assess the ability of regression models accounting for single and pairwise mutations to correctly approximate a complex quasi-empirical fitness landscape. We compare approximations based on various sampling regimes of an RNA landscape and find that the sampling regime strongly influences the quality of the regression. On the one hand it is generally impossible to generate sufficient samples to achieve a good approximation of the complete fitness landscape, and on the other hand systematic sampling schemes can only provide a good description of the immediate neighborhood of a sequence of interest. Nevertheless, we obtain a remarkably good and unbiased fit to the local landscape when using sequences from a population that has evolved under strong selection. Thus, current statistical methods can provide a good approximation to the landscape of naturally evolving populations. PMID:27189564
Fitting population models from field data
Emlen, J.M.; Freeman, D.C.; Kirchhoff, M.D.; Alados, C.L.; Escos, J.; Duda, J.J.
2003-01-01
The application of population and community ecology to solving real-world problems requires population and community dynamics models that reflect the myriad patterns of interaction among organisms and between the biotic and physical environments. Appropriate models are not hard to construct, but the experimental manipulations needed to evaluate their defining coefficients are often both time consuming and costly, and sometimes environmentally destructive, as well. In this paper we present an empirical approach for finding the coefficients of broadly inclusive models without the need for environmental manipulation, demonstrate the approach with both an animal and a plant example, and suggest possible applications. Software has been developed, and is available from the senior author, with a manual describing both field and analytic procedures.
MAPCLUS: A Mathematical Programming Approach to Fitting the ADCLUS Model.
ERIC Educational Resources Information Center
Arabie, Phipps
1980-01-01
A new computing algorithm, MAPCLUS (Mathematical Programming Clustering), for fitting the Shephard-Arabie ADCLUS (Additive Clustering) model is presented. Details and benefits of the algorithm are discussed. (Author/JKS)
A New Tradition To Fit the Model.
ERIC Educational Resources Information Center
Darnell, D. Roe; Rosenthal, Donna McCrohan
2001-01-01
Discusses Cerro Coso Community College in Ridgecrest (California), where 80-85 of all local jobs are with one employer, the China Lake Naval Air Weapons Station (NAWS). States that massive layoffs at NAWS inspired creative ways of rethinking the community college model at Cerro Coso, such as creating the nation's first computer graphics imagery…
Fitting ARMA Time Series by Structural Equation Models.
ERIC Educational Resources Information Center
van Buuren, Stef
1997-01-01
This paper outlines how the stationary ARMA (p,q) model (G. Box and G. Jenkins, 1976) can be specified as a structural equation model. Maximum likelihood estimates for the parameters in the ARMA model can be obtained by software for fitting structural equation models. The method is applied to three problem types. (SLD)
Relative and Absolute Fit Evaluation in Cognitive Diagnosis Modeling
ERIC Educational Resources Information Center
Chen, Jinsong; de la Torre, Jimmy; Zhang, Zao
2013-01-01
As with any psychometric models, the validity of inferences from cognitive diagnosis models (CDMs) determines the extent to which these models can be useful. For inferences from CDMs to be valid, it is crucial that the fit of the model to the data is ascertained. Based on a simulation study, this study investigated the sensitivity of various fit…
ERIC Educational Resources Information Center
Olsson, Ulf Henning; Troye, Sigurd Villads; Howell, Roy D.
1999-01-01
Used simulation to compare the ability of maximum likelihood (ML) and generalized least-squares (GLS) estimation to provide theoretic fit in models that are parsimonious representations of a true model. The better empirical fit obtained for GLS, compared with ML, was obtained at the cost of lower theoretic fit. (Author/SLD)
Asteroseismic model fitting by comparing ɛnℓ values
NASA Astrophysics Data System (ADS)
Roxburgh, Ian W.
2016-01-01
We present an asteroseismic model fitting algorithm based on comparing model and observed ɛℓ(ν) values defined in terms of frequencies by νnℓ = Δ [ n + ℓ/ 2 + ɛℓ(νnℓ) ] where Δ is an average large separation. We show that if two stellar models have the same interior structure but different outer layers then the difference between their ɛℓ(ν) values, interpolated to the same frequencies, collapses to a function only of frequency, independent of angular degree ℓ. The algorithm tests the goodness fit by comparing the difference in model and observed ɛ values after having subtracted off a best fit ℓ independent function of frequency ℱ(ν), and only requires interpolation in model values and not in observed values so the errors on the observed values are uncorrelated; it is independent of the n values assigned to the radial ordering of the frequencies and does not require the calculation of inner phase shifts of the model. We contrast this to a proposed direct frequency matching technique which minimises the difference between observed and model frequencies after having subtracted off an ℓ independent fit to these differences. We show this technique is flawed in principle, that all models with the same dimensionless structure but any mass and radius have the same quality of fit to an observed data set, and that it can give erroneous best fit models. We illustrate the epsilon matching technique by comparing stellar models and then apply it to data on HD 177153 (aka Perky). On comparing observations with a set of main sequence evolutionary models we find that models which satisfy constraints on the luminosity, radius, Δ, and on ɛ matching, have masses in the range 1.155 ± 0.035 M⊙ and ages in the range 4.486 ± 0.250 × 109 yr. Since the large separation and the radius are surface layer dependent we examine "pure surface layer independent" model fitting where the only constraints on the model fitting are on the luminosity and epsilon
Transit Model Fitting in the Kepler Science Operations Center Pipeline
NASA Astrophysics Data System (ADS)
Li, Jie; Burke, C. J.; Jenkins, J. M.; Quintana, E. V.; Rowe, J. F.; Seader, S. E.; Tenenbaum, P.; Twicken, J. D.
2012-05-01
We describe the algorithm and performance of the transit model fitting of the Kepler Science Operations Center (SOC) Pipeline. Light curves of long cadence targets are subjected to the Transiting Planet Search (TPS) component of the Kepler SOC Pipeline. Those targets for which a Threshold Crossing Event (TCE) is generated in the transit search are subsequently processed in the Data Validation (DV) component. The light curves may span one or more Kepler observing quarters, and data may not be available for any given target in all quarters. Transit model parameters are fitted in DV to transit-like signatures in the light curves of target stars with TCEs. The fitted parameters are used to generate a predicted light curve based on the transit model. The residual flux time series of the target star, with the predicted light curve removed, is fed back to TPS to search for additional TCEs. The iterative process of transit model fitting and transiting planet search continues until no TCE is generated from the residual flux time series or a planet candidate limit is reached. The transit model includes five parameters to be fitted: transit epoch time (i.e. central time of first transit), orbital period, impact parameter, ratio of planet radius to star radius and ratio of semi-major axis to star radius. The initial values of the fit parameters are determined from the TCE values provided by TPS. A limb darkening model is included in the transit model to generate the predicted light curve. The transit model fitting results are used in the diagnostic tests in DV, such as the centroid motion test, eclipsing binary discrimination tests, etc., which helps to validate planet candidates and identify false positive detections. Funding for the Kepler Mission has been provided by the NASA Science Mission Directorate.
Modeling battery life through changes in voltage fit coefficients
NASA Technical Reports Server (NTRS)
Fox, D.; Mcdermott, P.
1983-01-01
A number of 12 ampere-hour cells, nickel cadmium, were cycled under various conditions of temperature and depth of discharge. Using this data, it was confirmed that a five parameter fit equation could be used to model the data within a few millivolts. Both charge and discharge curves can be fit with accuracies in the range of one or two millivolts. The fit coefficients when plotted versus cycles show definite trends and patterns which can be used in an operational sense to predict battery voltage as a function of temperature and depth of discharge.
Atomic Data for X-ray Spectrum Synthesis: Sensitivity Analysis and Consequences for Spectral Fitting
NASA Astrophysics Data System (ADS)
Kallman, Timothy R.
2006-09-01
A great deal of work has been devoted to the accumulation of accurate quantities describing atomic processes for use in analysis of astrophysical spectra. But in many situations of interest the interpretation of a quantity which is observed, such as a line flux, depends on the results of a modeling- or spectrum synthesis code. The results of such a code depends in turn on many atomic rates or cross sections, and the sensitivity of the observable quantity on the various rates and cross sections may be non-linear and if so cannot easily be derived analytically. In such cases the most practical approach to understanding the sensitivity of observables to atomic cross sections is to perform numerical experiments, by calculating models with various rates perturbed by random (but known) factors. In addition, it is useful to compare the results of such experiments with some sample observations, in order to focus attention on the rates which are of the greatest relevance to real observations. I will present some attempts to carry out this program, focussing on two sample datasets taken with the Chandra HETG. I will discuss the sensitivity of synthetic spectra to atomic data affecting ionization balance, temperature, and line opacity or emissivity, and discuss the implications for the ultimate goal of inferring astrophysical parameters. In addition, I will discuss the likely effects on the ionization balance and spectrum synthesis due to the adoption of some recent calculations of dielectronic recombination rate coefficients.
Akaike information criterion to select well-fit resist models
NASA Astrophysics Data System (ADS)
Burbine, Andrew; Fryer, David; Sturtevant, John
2015-03-01
In the field of model design and selection, there is always a risk that a model is over-fit to the data used to train the model. A model is well suited when it describes the physical system and not the stochastic behavior of the particular data collected. K-fold cross validation is a method to check this potential over-fitting to the data by calibrating with k-number of folds in the data, typically between 4 and 10. Model training is a computationally expensive operation, however, and given a wide choice of candidate models, calibrating each one repeatedly becomes prohibitively time consuming. Akaike information criterion (AIC) is an information-theoretic approach to model selection based on the maximized log-likelihood for a given model that only needs a single calibration per model. It is used in this study to demonstrate model ranking and selection among compact resist modelforms that have various numbers and types of terms to describe photoresist behavior. It is shown that there is a good correspondence of AIC to K-fold cross validation in selecting the best modelform, and it is further shown that over-fitting is, in most cases, not indicated. In modelforms with more than 40 fitting parameters, the size of the calibration data set benefits from additional parameters, statistically validating the model complexity.
Twitter classification model: the ABC of two million fitness tweets.
Vickey, Theodore A; Ginis, Kathleen Martin; Dabrowski, Maciej
2013-09-01
The purpose of this project was to design and test data collection and management tools that can be used to study the use of mobile fitness applications and social networking within the context of physical activity. This project was conducted over a 6-month period and involved collecting publically shared Twitter data from five mobile fitness apps (Nike+, RunKeeper, MyFitnessPal, Endomondo, and dailymile). During that time, over 2.8 million tweets were collected, processed, and categorized using an online tweet collection application and a customized JavaScript. Using the grounded theory, a classification model was developed to categorize and understand the types of information being shared by application users. Our data show that by tracking mobile fitness app hashtags, a wealth of information can be gathered to include but not limited to daily use patterns, exercise frequency, location-based workouts, and overall workout sentiment. PMID:24073182
Statistics in asteroseismology: Evaluating confidence in stellar model fits
NASA Astrophysics Data System (ADS)
Johnson, Erik Stewart
We evaluate techniques presently used to match slates of stellar evolution models to asteroseismic observations by using numeric simulations of the model fits with randomly generated numbers. Measuring the quality of the fit between a simulated model and the star by a raw chi2 shows how well a reported model fit to a given star compares to a distribution of random model fits to the same star. The distribution of chi2 between "models" and simulated pulsations exhibits the behavior of a log-normal distribution, which suggests a link between the distribution and an analytic solution. Since the shape of the distribution strongly depends on the peculiar distribution of modes within the simulations, there appears to be no universal analytic quality-of-fit criterion, so evaluating seismic model fits must be done on a case--by--case basis. We also perform numeric simulations to determine the validity of spacings between pulsations by comparing the spacing between the observed modes of a given star to those between 106 sets of random numbers using the Q parameter of the Kolmogorov-Smirnov test. The observed periods in GD 358 and PG 1159--035 outperform these numeric simulations and validate their perceived spacings, while there is little support for spacings in PG 1219+534 or PG 0014+067. The best period spacing in BPM 37098 is marginally significant. The observed frequencies of eta Bootis outstrip random sets with an equal number of modes, but the modes are selectively chosen by the investigators from over 70 detected periodicities. When choosing the random data from sets of 70 values, the observed modes' spacings are reproducible by at least 2% of the random sets. Comparing asteroseismic data to random numbers statistically gauge the prominence of any possible spacing which removes another element of bias from asteroseismic analysis.
Eigen model with general fitness functions and degradation rates
NASA Astrophysics Data System (ADS)
Hu, Chin-Kun; Saakian, David B.
2006-03-01
We present an exact solution of Eigen's quasispecies model with a general degradation rate and fitness functions, including a square root decrease of fitness with increasing Hamming distance from the wild type. The found behavior of the model with a degradation rate is analogous to a viral quasi-species under attack by the immune system of the host. Our exact solutions also revise the known results of neutral networks in quasispecies theory. To explain the existence of mutants with large Hamming distances from the wild type, we propose three different modifications of the Eigen model: mutation landscape, multiple adjacent mutations, and frequency-dependent fitness in which the steady state solution shows a multi-center behavior.
Time-domain fitting of battery electrochemical impedance models
NASA Astrophysics Data System (ADS)
Alavi, S. M. M.; Birkl, C. R.; Howey, D. A.
2015-08-01
Electrochemical impedance spectroscopy (EIS) is an effective technique for diagnosing the behaviour of electrochemical devices such as batteries and fuel cells, usually by fitting data to an equivalent circuit model (ECM). The common approach in the laboratory is to measure the impedance spectrum of a cell in the frequency domain using a single sine sweep signal, then fit the ECM parameters in the frequency domain. This paper focuses instead on estimation of the ECM parameters directly from time-domain data. This may be advantageous for parameter estimation in practical applications such as automotive systems including battery-powered vehicles, where the data may be heavily corrupted by noise. The proposed methodology is based on the simplified refined instrumental variable for continuous-time fractional systems method ('srivcf'), provided by the Crone toolbox [1,2], combined with gradient-based optimisation to estimate the order of the fractional term in the ECM. The approach was tested first on synthetic data and then on real data measured from a 26650 lithium-ion iron phosphate cell with low-cost equipment. The resulting Nyquist plots from the time-domain fitted models match the impedance spectrum closely (much more accurately than when a Randles model is assumed), and the fitted parameters as separately determined through a laboratory potentiostat with frequency domain fitting match to within 13%.
Evolution in random fitness landscapes: the infinite sites model
NASA Astrophysics Data System (ADS)
Park, Su-Chan; Krug, Joachim
2008-04-01
We consider the evolution of an asexually reproducing population in an uncorrelated random fitness landscape in the limit of infinite genome size, which implies that each mutation generates a new fitness value drawn from a probability distribution g(w). This is the finite population version of Kingman's house of cards model (Kingman 1978 J. Appl. Probab. 15 1). In contrast to Kingman's work, the focus here is on unbounded distributions g(w) which lead to an indefinite growth of the population fitness. The model is solved analytically in the limit of infinite population size N \\to \\infty and simulated numerically for finite N. When the genome-wide mutation probability U is small, the long-time behavior of the model reduces to a point process of fixation events, which is referred to as a diluted record process (DRP). The DRP is similar to the standard record process except that a new record candidate (a number that exceeds all previous entries in the sequence) is accepted only with a certain probability that depends on the values of the current record and the candidate. We develop a systematic analytic approximation scheme for the DRP. At finite U the fitness frequency distribution of the population decomposes into a stationary part due to mutations and a traveling wave component due to selection, which is shown to imply a reduction of the mean fitness by a factor of 1-U compared to the U \\to 0 limit.
Prill, Dragica; Juhás, Pavol; Billinge, Simon J L; Schmidt, Martin U
2016-01-01
A method towards the solution and refinement of organic crystal structures by fitting to the atomic pair distribution function (PDF) is developed. Approximate lattice parameters and molecular geometry must be given as input. The molecule is generally treated as a rigid body. The positions and orientations of the molecules inside the unit cell are optimized starting from random values. The PDF is obtained from carefully measured X-ray powder diffraction data. The method resembles `real-space' methods for structure solution from powder data, but works with PDF data instead of the diffraction pattern itself. As such it may be used in situations where the organic compounds are not long-range-ordered, are poorly crystalline, or nanocrystalline. The procedure was applied to solve and refine the crystal structures of quinacridone (β phase), naphthalene and allopurinol. In the case of allopurinol it was even possible to successfully solve and refine the structure in P1 with four independent molecules. As an example of a flexible molecule, the crystal structure of paracetamol was refined using restraints for bond lengths, bond angles and selected torsion angles. In all cases, the resulting structures are in excellent agreement with structures from single-crystal data. PMID:26697868
Prill, Dragica; Juhas, Pavol; Billinge, Simon J. L.; Schmidt, Martin U.
2016-01-01
In this study, a method towards the solution and refinement of organic crystal structures by fitting to the atomic pair distribution function (PDF) is developed. Approximate lattice parameters and molecular geometry must be given as input. The molecule is generally treated as a rigid body. The positions and orientations of the molecules inside the unit cell are optimized starting from random values. The PDF is obtained from carefully measured X-ray powder diffraction data. The method resembles `real-space' methods for structure solution from powder data, but works with PDF data instead of the diffraction pattern itself. As such it may bemore » used in situations where the organic compounds are not long-range-ordered, are poorly crystalline, or nanocrystalline. The procedure was applied to solve and refine the crystal structures of quinacridone (β phase), naphthalene and allopurinol. In the case of allopurinol it was even possible to successfully solve and refine the structure in P1 with four independent molecules. As an example of a flexible molecule, the crystal structure of paracetamol was refined using restraints for bond lengths, bond angles and selected torsion angles. In all cases, the resulting structures are in excellent agreement with structures from single-crystal data.« less
Prill, Dragica; Juhas, Pavol; Billinge, Simon J. L.; Schmidt, Martin U.
2016-01-01
In this study, a method towards the solution and refinement of organic crystal structures by fitting to the atomic pair distribution function (PDF) is developed. Approximate lattice parameters and molecular geometry must be given as input. The molecule is generally treated as a rigid body. The positions and orientations of the molecules inside the unit cell are optimized starting from random values. The PDF is obtained from carefully measured X-ray powder diffraction data. The method resembles `real-space' methods for structure solution from powder data, but works with PDF data instead of the diffraction pattern itself. As such it may be used in situations where the organic compounds are not long-range-ordered, are poorly crystalline, or nanocrystalline. The procedure was applied to solve and refine the crystal structures of quinacridone (β phase), naphthalene and allopurinol. In the case of allopurinol it was even possible to successfully solve and refine the structure in P1 with four independent molecules. As an example of a flexible molecule, the crystal structure of paracetamol was refined using restraints for bond lengths, bond angles and selected torsion angles. In all cases, the resulting structures are in excellent agreement with structures from single-crystal data.
On the accuracy and fitting of transversely isotropic material models.
Feng, Yuan; Okamoto, Ruth J; Genin, Guy M; Bayly, Philip V
2016-08-01
Fiber reinforced structures are central to the form and function of biological tissues. Hyperelastic, transversely isotropic material models are used widely in the modeling and simulation of such tissues. Many of the most widely used models involve strain energy functions that include one or both pseudo-invariants (I4 or I5) to incorporate energy stored in the fibers. In a previous study we showed that both of these invariants must be included in the strain energy function if the material model is to reduce correctly to the well-known framework of transversely isotropic linear elasticity in the limit of small deformations. Even with such a model, fitting of parameters is a challenge. Here, by evaluating the relative roles of I4 and I5 in the responses to simple loadings, we identify loading scenarios in which previous models accounting for only one of these invariants can be expected to provide accurate estimation of material response, and identify mechanical tests that have special utility for fitting of transversely isotropic constitutive models. Results provide guidance for fitting of transversely isotropic constitutive models and for interpretation of the predictions of these models. PMID:27136091
The Gold Medal Fitness Program: A Model for Teacher Change
ERIC Educational Resources Information Center
Wright, Jan; Konza, Deslea; Hearne, Doug; Okely, Tony
2008-01-01
Background: Following the 2000 Sydney Olympics, the NSW Premier, Mr Bob Carr, launched a school-based initiative in NSW government primary schools called the "Gold Medal Fitness Program" to encourage children to be fitter and more active. The Program was introduced into schools through a model of professional development, "Quality Teaching and…
The conical fit approach to modeling ionospheric total electron content
NASA Technical Reports Server (NTRS)
Sparks, L.; Komjathy, A.; Mannucci, A. J.
2002-01-01
The Global Positioning System (GPS) can be used to measure the integrated electron density along raypaths between satellites and receivers. Such measurements may, in turn, be used to construct regional and global maps of the ionospheric total electron content (TEC). Maps are generated by fitting measurements to an assumed ionospheric model.
Fuzzy Partition Models for Fitting a Set of Partitions.
ERIC Educational Resources Information Center
Gordon, A. D.; Vichi, M.
2001-01-01
Describes methods for fitting a fuzzy consensus partition to a set of partitions of the same set of objects. Describes and illustrates three models defining median partitions and compares these methods to an alternative approach to obtaining a consensus fuzzy partition. Discusses interesting differences in the results. (SLD)
Multidimensional Rasch Model Information-Based Fit Index Accuracy
ERIC Educational Resources Information Center
Harrell-Williams, Leigh M.; Wolfe, Edward W.
2013-01-01
Most research on confirmatory factor analysis using information-based fit indices (Akaike information criterion [AIC], Bayesian information criteria [BIC], bias-corrected AIC [AICc], and consistent AIC [CAIC]) has used a structural equation modeling framework. Minimal research has been done concerning application of these indices to item response…
Statistical assessment of model fit for synthetic aperture radar data
NASA Astrophysics Data System (ADS)
DeVore, Michael D.; O'Sullivan, Joseph A.
2001-08-01
Parametric approaches to problems of inference from observed data often rely on assumed probabilistic models for the data which may be based on knowledge of the physics of the data acquisition. Given a rich enough collection of sample data, the validity of those assumed models can be assessed in a statistical hypothesis testing framework using any of a number of goodness-of-fit tests developed over the last hundred years for this purpose. Such assessments can be used both to compare alternate models for observed data and to help determine the conditions under which a given model breaks down. We apply three such methods, the (chi) 2 test of Karl Pearson, Kolmogorov's goodness-of-fit test, and the D'Agostino-Pearson test for normality, to quantify how well the data fit various models for synthetic aperture radar (SAR) images. The results of these tests are used to compare a conditionally Gaussian model for complex-valued SAR pixel values, a conditionally log-normal model for SAR pixel magnitudes, and a conditionally normal model for SAR pixel quarter-power values. Sample data for these tests are drawn from the publicly released MSTAR dataset.
Nagaoka's atomic model and hyperfine interactions.
Inamura, Takashi T
2016-01-01
The prevailing view of Nagaoka's "Saturnian" atom is so misleading that today many people have an erroneous picture of Nagaoka's vision. They believe it to be a system involving a 'giant core' with electrons circulating just outside. Actually, though, in view of the Coulomb potential related to the atomic nucleus, Nagaoka's model is exactly the same as Rutherford's. This is true of the Bohr atom, too. To give proper credit, Nagaoka should be remembered together with Rutherford and Bohr in the history of the atomic model. It is also pointed out that Nagaoka was a pioneer of understanding hyperfine interactions in order to study nuclear structure. PMID:27063182
The Hydrogen Atom: The Rutherford Model
NASA Astrophysics Data System (ADS)
Tilton, Homer Benjamin
1996-06-01
Early this century Ernest Rutherford established the nuclear model of the hydrogen atom, presently taught as representing the best visual model after modification by Niels Bohr and Arnold Sommerfeld. It replaced the so-called "plum pudding" model of J. J. Thomson which held sway previously. While the Rutherford model represented a large step forward in our understanding of the hydrogen atom, questions remained, and still do.
The Completeness Criterion in Atomic Modeling
NASA Astrophysics Data System (ADS)
Liedahl, Duane A.
2000-10-01
I discuss two variations on the completeness theme in atomic modeling; missing lines as they affect the performance of spectral synthesis codes, and missing configurations as they affect the theoretical emissivities of bright lines, with emphasis on the latter. It is shown that the detrimental effects of working with incomplete atomic models can overshadow those brought about by working with less-than-perfect atomic rates. Atomic models can be brought up to an acceptable level of completeness in a fairly straightforward manner, and on a reasonably short timescale, whereas the long-term goal of comprehensive accuracy is unlikely to be reached on the timescale of the current generation of X-ray observatories. A near-term, albeit imperfect, solution is to hybridize atomic models used to synthesize spectra. A hybrid atomic model is one for which a large-scale atomic model, in which completeness is achieved at the expense of accuracy, is augmented with more accurate atomic quantities as they become available.
Assessing the fit of site-occupancy models
MacKenzie, D.I.; Bailey, L.L.
2004-01-01
Few species are likely to be so evident that they will always be detected at a site when present. Recently a model has been developed that enables estimation of the proportion of area occupied, when the target species is not detected with certainty. Here we apply this modeling approach to data collected on terrestrial salamanders in the Plethodon glutinosus complex in the Great Smoky Mountains National Park, USA, and wish to address the question 'how accurately does the fitted model represent the data?' The goodness-of-fit of the model needs to be assessed in order to make accurate inferences. This article presents a method where a simple Pearson chi-square statistic is calculated and a parametric bootstrap procedure is used to determine whether the observed statistic is unusually large. We found evidence that the most global model considered provides a poor fit to the data, hence estimated an overdispersion factor to adjust model selection procedures and inflate standard errors. Two hypothetical datasets with known assumption violations are also analyzed, illustrating that the method may be used to guide researchers to making appropriate inferences. The results of a simulation study are presented to provide a broader view of the methods properties.
LITpro: a model fitting software for optical interferometry
NASA Astrophysics Data System (ADS)
Tallon-Bosc, I.; Tallon, M.; Thiébaut, E.; Béchet, C.; Mella, G.; Lafrasse, S.; Chesneau, O.; Domiciano de Souza, A.; Duvert, G.; Mourard, D.; Petrov, R.; Vannier, M.
2008-07-01
LITpro is a software for fitting models on data obtained from various stellar optical interferometers, like the VLTI. As a baseline, for modeling the object, it provides a set of elementary geometrical and center-to-limb darkening functions, all combinable together. But it is also designed to make very easy the implementation of more specific models with their own parameters, to be able to use models closer to astrophysical considerations. So LITpro only requires the modeling functions to compute the Fourier transform of the object at given spatial frequencies, and wavelengths and time if needed. From this, LITpro computes all the necessary quantities as needed (e.g. visibilities, spectral energy distribution, partial derivatives of the model, map of the object model). The fitting engine, especially designed for this kind of optimization, is based on a modified Levenberg-Marquardt algorithm and has been successfully tested on real data in a prototype version. It includes a Trust Region Method, minimizing a heterogeneous non-linear and non-convex criterion and allows the user to set boundaries on free parameters. From a robust local minimization algorithm and a starting points strategy, a global optimization solution is effectively achieved. Tools have been developped to help users to find the global minimum. LITpro is also designed for performing fitting on heterogeneous data. It will be shown, on an example, how it fits simultaneously interferometric data and spectral energy distribution, with some benefits on the reliability of the solution and a better estimation of errors and correlations on the parameters. That is indeed necessary since present interferometric data are generally multi-wavelengths.
Methodology for fitting and updating predictive accident models with trend.
Connors, Richard D; Maher, Mike; Wood, Alan; Mountain, Linda; Ropkins, Karl
2013-07-01
Reliable predictive accident models (PAMs) (also referred to as Safety Performance Functions (SPFs)) have a variety of important uses in traffic safety research and practice. They are used to help identify sites in need of remedial treatment, in the design of transport schemes to assess safety implications, and to estimate the effectiveness of remedial treatments. The PAMs currently in use in the UK are now quite old; the data used in their development was gathered up to 30 years ago. Many changes have occurred over that period in road and vehicle design, in road safety campaigns and legislation, and the national accident rate has fallen substantially. It seems unlikely that these ageing models can be relied upon to provide accurate and reliable predictions of accident frequencies on the roads today. This paper addresses a number of methodological issues that arise in seeking practical and efficient ways to update PAMs, whether by re-calibration or by re-fitting. Models for accidents on rural single carriageway roads have been chosen to illustrate these issues, including the choice of distributional assumption for overdispersion, the choice of goodness of fit measures, questions of independence between observations in different years, and between links on the same scheme, the estimation of trends in the models, the uncertainty of predictions, as well as considerations about the most efficient and convenient ways to fit the required models. PMID:23612560
Atomic modeling of the plasma EUV sources
NASA Astrophysics Data System (ADS)
Sasaki, Akira; Sunahara, Atsushi; Furukawa, Hiroyuki; Nishihara, Katsunobu; Nishikawa, Takeshi; Koike, Fumihiro; Tanuma, Hajime
2009-09-01
We present the development of population kinetics models for tin plasmas that can be employed to design an EUV source for microlithography. The atomic kinetic code is constrained for the requirement that the model must be able to calculate spectral emissivity and opacity that can be used in radiation hydrodynamic simulations. Methods to develop compact and reliable atomic model with an appropriate set of atomic states are discussed. Specifically, after investigation of model dependencies and comparison experiment, we improve the effect of configuration interaction and the treatment of satellite lines. Using the present atomic model we discuss the temperature and density dependencies of the emissivity, as well as conditions necessary to obtain high efficiency EUV power at λ = 13.5 nm.
Model fitting and inference under Latent Equilibrium Processes
Bhattacharya, Sourabh; Gelfand, Alan E.; Holsinger, Kent E.
2008-01-01
This paper presents a methodology for model fitting and inference in the context of Bayesian models of the type f(Y | X, θ)f(X | θ)f(θ), where Y is the (set of) observed data, θ is a set of model parameters and X is an unobserved (latent) stationary stochastic process induced by the first order transition model f(X(t+1) | X(t), θ), where X(t) denotes the state of the process at time (or generation) t. The crucial feature of the above type of model is that, given θ, the transition model f(X(t+1) | X(t), θ) is known but the distribution of the stochastic process in equilibrium, that is f(X | θ), is, except in very special cases, intractable, hence unknown. A further point to note is that the data Y has been assumed to be observed when the underlying process is in equilibrium. In other words, the data is not collected dynamically over time. We refer to such specification as a latent equilibrium process (LEP) model. It is motivated by problems in population genetics (though other applications are discussed), where it is of interest to learn about parameters such as mutation and migration rates and population sizes, given a sample of allele frequencies at one or more loci. In such problems it is natural to assume that the distribution of the observed allele frequencies depends on the true (unobserved) population allele frequencies, whereas the distribution of the true allele frequencies is only indirectly specified through a transition model. As a hierarchical specification, it is natural to fit the LEP within a Bayesian framework. Fitting such models is usually done via Markov chain Monte Carlo (MCMC). However, we demonstrate that, in the case of LEP models, implementation of MCMC is far from straightforward. The main contribution of this paper is to provide a methodology to implement MCMC for LEP models. We demonstrate our approach in population genetics problems with both simulated and real data sets. The resultant model fitting is computationally intensive
Atmospheric Turbulence Modeling for Aerospace Vehicles: Fractional Order Fit
NASA Technical Reports Server (NTRS)
Kopasakis, George (Inventor)
2015-01-01
An improved model for simulating atmospheric disturbances is disclosed. A scale Kolmogorov spectral may be scaled to convert the Kolmogorov spectral into a finite energy von Karman spectral and a fractional order pole-zero transfer function (TF) may be derived from the von Karman spectral. Fractional order atmospheric turbulence may be approximated with an integer order pole-zero TF fit, and the approximation may be stored in memory.
ERIC Educational Resources Information Center
Thissen, David
2013-01-01
In this commentary, David Thissen states that "Goodness-of-fit assessment for IRT models is maturing; it has come a long way from zero." Thissen then references prior works on "goodness of fit" in the index of Lord and Novick's (1968) classic text; Yen (1984); Drasgow, Levine, Tsien, Williams, and Mead (1995); Chen and…
Blanquart, François; Bataillon, Thomas
2016-01-01
The fitness landscape defines the relationship between genotypes and fitness in a given environment and underlies fundamental quantities such as the distribution of selection coefficient and the magnitude and type of epistasis. A better understanding of variation in landscape structure across species and environments is thus necessary to understand and predict how populations will adapt. An increasing number of experiments investigate the properties of fitness landscapes by identifying mutations, constructing genotypes with combinations of these mutations, and measuring the fitness of these genotypes. Yet these empirical landscapes represent a very small sample of the vast space of all possible genotypes, and this sample is often biased by the protocol used to identify mutations. Here we develop a rigorous statistical framework based on Approximate Bayesian Computation to address these concerns and use this flexible framework to fit a broad class of phenotypic fitness models (including Fisher’s model) to 26 empirical landscapes representing nine diverse biological systems. Despite uncertainty owing to the small size of most published empirical landscapes, the inferred landscapes have similar structure in similar biological systems. Surprisingly, goodness-of-fit tests reveal that this class of phenotypic models, which has been successful so far in interpreting experimental data, is a plausible in only three of nine biological systems. More precisely, although Fisher’s model was able to explain several statistical properties of the landscapes—including the mean and SD of selection and epistasis coefficients—it was often unable to explain the full structure of fitness landscapes. PMID:27052568
Chapman, Michael S.; Trzynka, Andrew; Chapman, Brynmor K.
2013-01-01
When refining the fit of component atomic structures into electron microscopic reconstructions, use of a resolution-dependent atomic density function makes it possible to jointly optimize the atomic model and imaging parameters of the microscope. Atomic density is calculated by one-dimensional Fourier transform of atomic form factors convoluted with a microscope envelope correction and a low-pass filter, allowing refinement of imaging parameters such as resolution, by optimizing the agreement of calculated and experimental maps. A similar approach allows refinement of atomic displacement parameters, providing indications of molecular flexibility even at low resolution. A modest improvement in atomic coordinates is possible following optimization of these additional parameters. Methods have been implemented in a Python program that can be used in stand-alone mode for rigid-group refinement, or embedded in other optimizers for flexible refinement with stereochemical restraints. The approach is demonstrated with refinements of virus and chaperonin structures at resolutions of 9 through 4.5 Å, representing regimes where rigid-group and fully flexible parameterizations are appropriate. Through comparisons to known crystal structures, flexible fitting by RSRef is shown to be an improvement relative to other methods and to generate models with all-atom rms accuracies of 1.5–2.5 Å at resolutions of 4.5–6 Å. PMID:23376441
Chapman, Michael S; Trzynka, Andrew; Chapman, Brynmor K
2013-04-01
When refining the fit of component atomic structures into electron microscopic reconstructions, use of a resolution-dependent atomic density function makes it possible to jointly optimize the atomic model and imaging parameters of the microscope. Atomic density is calculated by one-dimensional Fourier transform of atomic form factors convoluted with a microscope envelope correction and a low-pass filter, allowing refinement of imaging parameters such as resolution, by optimizing the agreement of calculated and experimental maps. A similar approach allows refinement of atomic displacement parameters, providing indications of molecular flexibility even at low resolution. A modest improvement in atomic coordinates is possible following optimization of these additional parameters. Methods have been implemented in a Python program that can be used in stand-alone mode for rigid-group refinement, or embedded in other optimizers for flexible refinement with stereochemical restraints. The approach is demonstrated with refinements of virus and chaperonin structures at resolutions of 9 through 4.5 Å, representing regimes where rigid-group and fully flexible parameterizations are appropriate. Through comparisons to known crystal structures, flexible fitting by RSRef is shown to be an improvement relative to other methods and to generate models with all-atom rms accuracies of 1.5-2.5 Å at resolutions of 4.5-6 Å. PMID:23376441
Bayesian Data-Model Fit Assessment for Structural Equation Modeling
ERIC Educational Resources Information Center
Levy, Roy
2011-01-01
Bayesian approaches to modeling are receiving an increasing amount of attention in the areas of model construction and estimation in factor analysis, structural equation modeling (SEM), and related latent variable models. However, model diagnostics and model criticism remain relatively understudied aspects of Bayesian SEM. This article describes…
Goodness-of-fit diagnostics for Bayesian hierarchical models.
Yuan, Ying; Johnson, Valen E
2012-03-01
This article proposes methodology for assessing goodness of fit in Bayesian hierarchical models. The methodology is based on comparing values of pivotal discrepancy measures (PDMs), computed using parameter values drawn from the posterior distribution, to known reference distributions. Because the resulting diagnostics can be calculated from standard output of Markov chain Monte Carlo algorithms, their computational costs are minimal. Several simulation studies are provided, each of which suggests that diagnostics based on PDMs have higher statistical power than comparable posterior-predictive diagnostic checks in detecting model departures. The proposed methodology is illustrated in a clinical application; an application to discrete data is described in supplementary material. PMID:22050079
Bosone, Lucia; Martinez, Frédéric; Kalampalikis, Nikos
2015-04-01
In health-promotional campaigns, positive and negative role models can be deployed to illustrate the benefits or costs of certain behaviors. The main purpose of this article is to investigate why, how, and when exposure to role models strengthens the persuasiveness of a message, according to regulatory fit theory. We argue that exposure to a positive versus a negative model activates individuals' goals toward promotion rather than prevention. By means of two experiments, we demonstrate that high levels of persuasion occur when a message advertising healthy dietary habits offers a regulatory fit between its framing and the described role model. Our data also establish that the effects of such internal regulatory fit by vicarious experience depend on individuals' perceptions of response-efficacy and self-efficacy. Our findings constitute a significant theoretical complement to previous research on regulatory fit and contain valuable practical implications for health-promotional campaigns. PMID:25680684
Testing goodness of fit of parametric models for censored data.
Nysen, Ruth; Aerts, Marc; Faes, Christel
2012-09-20
We propose and study a goodness-of-fit test for left-censored, right-censored, and interval-censored data assuming random censorship. Main motivation comes from dietary exposure assessment in chemical risk assessment, where the determination of an appropriate distribution for concentration data is of major importance. We base the new goodness-of-fit test procedure proposed in this paper on the order selection test. As part of the testing procedure, we extend the null model to a series of nested alternative models for censored data. Then, we use a modified AIC model selection to select the best model to describe the data. If a model with one or more extra parameters is selected, then we reject the null hypothesis. As an alternative to the use of the asymptotic null distribution of the test statistic, we define a bootstrap-based procedure. We illustrate the applicability of the test procedure on data of cadmium concentrations and on data from the Signal Tandmobiel study and demonstrate its performance characteristics through simulation studies. PMID:22714389
ERIC Educational Resources Information Center
Tay, Louis; Ali, Usama S.; Drasgow, Fritz; Williams, Bruce
2011-01-01
This study investigated the relative model-data fit of an ideal point item response theory (IRT) model (the generalized graded unfolding model [GGUM]) and dominance IRT models (e.g., the two-parameter logistic model [2PLM] and Samejima's graded response model [GRM]) to simulated dichotomous and polytomous data generated from each of these models.…
Rapid world modeling: Fitting range data to geometric primitives
Feddema, J.; Little, C.
1996-12-31
For the past seven years, Sandia National Laboratories has been active in the development of robotic systems to help remediate DOE`s waste sites and decommissioned facilities. Some of these facilities have high levels of radioactivity which prevent manual clean-up. Tele-operated and autonomous robotic systems have been envisioned as the only suitable means of removing the radioactive elements. World modeling is defined as the process of creating a numerical geometric model of a real world environment or workspace. This model is often used in robotics to plan robot motions which perform a task while avoiding obstacles. In many applications where the world model does not exist ahead of time, structured lighting, laser range finders, and even acoustical sensors have been used to create three dimensional maps of the environment. These maps consist of thousands of range points which are difficult to handle and interpret. This paper presents a least squares technique for fitting range data to planar and quadric surfaces, including cylinders and ellipsoids. Once fit to these primitive surfaces, the amount of data associated with a surface is greatly reduced up to three orders of magnitude, thus allowing for more rapid handling and analysis of world data.
Issues in Evaluating Model Fit With Missing Data
ERIC Educational Resources Information Center
Davey, Adam
2005-01-01
Effects of incomplete data on fit indexes remain relatively unexplored. We evaluate a wide set of fit indexes (?[squared], root mean squared error of appproximation, Normed Fit Index [NFI], Tucker-Lewis Index, comparative fit index, gamma-hat, and McDonald's Centrality Index) varying conditions of sample size (100-1,000 in increments of 50),…
Ion-Atom and Atom-Atom Collisional Processes and Modeling of Stellar Atmospheres
NASA Astrophysics Data System (ADS)
Mihajlov, A. A.; Ignjatovic, Lj. M.; Sreckovic, V. A.; Dimitrijevic, M. S.; Dimitrijevic, M. S.
2015-09-01
We report the results obtained in our previous works on the influence of two groups of collisional processes (ion--atom and atom--atom) on the optical and kinetic properties of weakly ionised plasma. The first group includes radiative processes of the photodissociation/association type and radiative charge exchange, the second one -- chemi-ionisation/recombination processes. The effect of the radiative processed is assessed by comparing their intensities with those of the known competing processed in application to the solar photosphere and to the photospheres of DB white dwarfs. The studied chemi-ionisation/recombination processes are considered from the viewpoint of their influence on the populations of the excited states of the hydrogen atom (the Sun and an M-type red dwarf with an effective temperature of 3800~K) and helium atom (DB white dwarfs). The effect of these processes on the populations of the excited states of the hydrogen atom has been studied using the PHOENIX code, which generates the model of the considered atmosphere. The reported results demonstrate the unquestionable influence of the considered radiative and chemi- ionisation/recombination processes on the optical properties and on the kinetics of the weakly ionised layers in stellar atmospheres. It can be expected that the reported results will be a sufficient reason for including these processes in the models of stellar atmospheres.
Tight Binding Models in Cold Atoms Physics
NASA Astrophysics Data System (ADS)
Zakrzewski, J.
2007-05-01
Cold atomic gases placed in optical lattice potentials offer a unique tool to study simple tight binding models. Both the standard cases known from the condensed matter theory as well as novel situations may be addressed. Cold atoms setting allows for a precise control of parameters of the systems discussed, stimulating new questions and problems. The attempts to treat disorder in a controlled fashion are addressed in detail.
Effect of the Number of Variables on Measures of Fit in Structural Equation Modeling.
ERIC Educational Resources Information Center
Kenny, David A.; McCoach, D. Betsy
2003-01-01
Used three approaches to understand the effect of the number of variables in the model on model fit in structural equation modeling through computer simulation. Developed a simple formula for the theoretical value of the comparative fit index. (SLD)
HIBAYES: Global 21-cm Bayesian Monte-Carlo Model Fitting
NASA Astrophysics Data System (ADS)
Zwart, Jonathan T. L.; Price, Daniel; Bernardi, Gianni
2016-06-01
HIBAYES implements fully-Bayesian extraction of the sky-averaged (global) 21-cm signal from the Cosmic Dawn and Epoch of Reionization in the presence of foreground emission. User-defined likelihood and prior functions are called by the sampler PyMultiNest (ascl:1606.005) in order to jointly explore the full (signal plus foreground) posterior probability distribution and evaluate the Bayesian evidence for a given model. Implemented models, for simulation and fitting, include gaussians (HI signal) and polynomials (foregrounds). Some simple plotting and analysis tools are supplied. The code can be extended to other models (physical or empirical), to incorporate data from other experiments, or to use alternative Monte-Carlo sampling engines as required.
An NCME Instructional Module on Item-Fit Statistics for Item Response Theory Models
ERIC Educational Resources Information Center
Ames, Allison J.; Penfield, Randall D.
2015-01-01
Drawing valid inferences from item response theory (IRT) models is contingent upon a good fit of the data to the model. Violations of model-data fit have numerous consequences, limiting the usefulness and applicability of the model. This instructional module provides an overview of methods used for evaluating the fit of IRT models. Upon completing…
Assessing Model Data Fit of Unidimensional Item Response Theory Models in Simulated Data
ERIC Educational Resources Information Center
Kose, Ibrahim Alper
2014-01-01
The purpose of this paper is to give an example of how to assess the model-data fit of unidimensional IRT models in simulated data. Also, the present research aims to explain the importance of fit and the consequences of misfit by using simulated data sets. Responses of 1000 examinees to a dichotomously scoring 20 item test were simulated with 25…
Empirical fitness models for hepatitis C virus immunogen design
NASA Astrophysics Data System (ADS)
Hart, Gregory R.; Ferguson, Andrew L.
2015-12-01
Hepatitis C virus (HCV) afflicts 170 million people worldwide, 2%-3% of the global population, and kills 350 000 each year. Prophylactic vaccination offers the most realistic and cost effective hope of controlling this epidemic in the developing world where expensive drug therapies are not available. Despite 20 years of research, the high mutability of the virus and lack of knowledge of what constitutes effective immune responses have impeded development of an effective vaccine. Coupling data mining of sequence databases with spin glass models from statistical physics, we have developed a computational approach to translate clinical sequence databases into empirical fitness landscapes quantifying the replicative capacity of the virus as a function of its amino acid sequence. These landscapes explicitly connect viral genotype to phenotypic fitness, and reveal vulnerable immunological targets within the viral proteome that can be exploited to rationally design vaccine immunogens. We have recovered the empirical fitness landscape for the HCV RNA-dependent RNA polymerase (protein NS5B) responsible for viral genome replication, and validated the predictions of our model by demonstrating excellent accord with experimental measurements and clinical observations. We have used our landscapes to perform exhaustive in silico screening of 16.8 million T-cell immunogen candidates to identify 86 optimal formulations. By reducing the search space of immunogen candidates by over five orders of magnitude, our approach can offer valuable savings in time, expense, and labor for experimental vaccine development and accelerate the search for a HCV vaccine. Abbreviations: HCV—hepatitis C virus, HLA—human leukocyte antigen, CTL—cytotoxic T lymphocyte, NS5B—nonstructural protein 5B, MSA—multiple sequence alignment, PEG-IFN—pegylated interferon.
ERIC Educational Resources Information Center
Raykov, Tenko; Lee, Chun-Lung; Marcoulides, George A.; Chang, Chi
2013-01-01
The relationship between saturated path-analysis models and their fit to data is revisited. It is demonstrated that a saturated model need not fit perfectly or even well a given data set when fit to the raw data is examined, a criterion currently frequently overlooked by researchers utilizing path analysis modeling techniques. The potential of…
Left Ventricle Segmentation Using Model Fitting and Active Surfaces
Tay, Peter C.; Li, Bing; Garson, Chris D.; Acton, Scott T.; Hossack, John A.
2010-01-01
A method to perform 4D (3D over time) segmentation of the left ventricle of a mouse heart using a set of B mode cine slices acquired in vivo from a series of short axis scans is described. We incorporate previously suggested methods such as temporal propagation, the gradient vector flow active surface, superquadric models, etc. into our proposed 4D segmentation of the left ventricle. The contributions of this paper are incorporation of a novel despeckling method and the use of locally fitted superellipsoid models to provide a better initialization for the active surface segmentation algorithm. Average distances of the improved surface segmentation to a manually segmented surface throughout the entire cardiac cycle and cross-sectional contours are provided to demonstrate the improvements produced by the proposed 4D segmentation. PMID:20300558
Strategies for fitting nonlinear ecological models in R, AD Model Builder, and BUGS
Bolker, Benjamin M.; Gardner, Beth; Maunder, Mark; Berg, Casper W.; Brooks, Mollie; Comita, Liza; Crone, Elizabeth; Cubaynes, Sarah; Davies, Trevor; de Valpine, Perry; Ford, Jessica; Gimenez, Olivier; Kéry, Marc; Kim, Eun Jung; Lennert-Cody, Cleridy; Magunsson, Arni; Martell, Steve; Nash, John; Nielson, Anders; Regentz, Jim; Skaug, Hans; Zipkin, Elise
2013-01-01
1. Ecologists often use nonlinear fitting techniques to estimate the parameters of complex ecological models, with attendant frustration. This paper compares three open-source model fitting tools and discusses general strategies for defining and fitting models. 2. R is convenient and (relatively) easy to learn, AD Model Builder is fast and robust but comes with a steep learning curve, while BUGS provides the greatest flexibility at the price of speed. 3. Our model-fitting suggestions range from general cultural advice (where possible, use the tools and models that are most common in your subfield) to specific suggestions about how to change the mathematical description of models to make them more amenable to parameter estimation. 4. A companion web site (https://groups.nceas.ucsb.edu/nonlinear-modeling/projects) presents detailed examples of application of the three tools to a variety of typical ecological estimation problems; each example links both to a detailed project report and to full source code and data.
The FIT Model - Fuel-cycle Integration and Tradeoffs
Steven J. Piet; Nick R. Soelberg; Samuel E. Bays; Candido Pereira; Layne F. Pincock; Eric L. Shaber; Meliisa C Teague; Gregory M Teske; Kurt G Vedros
2010-09-01
All mass streams from fuel separation and fabrication are products that must meet some set of product criteria – fuel feedstock impurity limits, waste acceptance criteria (WAC), material storage (if any), or recycle material purity requirements such as zirconium for cladding or lanthanides for industrial use. These must be considered in a systematic and comprehensive way. The FIT model and the “system losses study” team that developed it [Shropshire2009, Piet2010] are an initial step by the FCR&D program toward a global analysis that accounts for the requirements and capabilities of each component, as well as major material flows within an integrated fuel cycle. This will help the program identify near-term R&D needs and set longer-term goals. The question originally posed to the “system losses study” was the cost of separation, fuel fabrication, waste management, etc. versus the separation efficiency. In other words, are the costs associated with marginal reductions in separations losses (or improvements in product recovery) justified by the gains in the performance of other systems? We have learned that that is the wrong question. The right question is: how does one adjust the compositions and quantities of all mass streams, given uncertain product criteria, to balance competing objectives including cost? FIT is a method to analyze different fuel cycles using common bases to determine how chemical performance changes in one part of a fuel cycle (say used fuel cooling times or separation efficiencies) affect other parts of the fuel cycle. FIT estimates impurities in fuel and waste via a rough estimate of physics and mass balance for a set of technologies. If feasibility is an issue for a set, as it is for “minimum fuel treatment” approaches such as melt refining and AIROX, it can help to make an estimate of how performances would have to change to achieve feasibility.
Robust Fitting of a Weibull Model with Optional Censoring
Yang, Jingjing; Scott, David W.
2013-01-01
The Weibull family is widely used to model failure data, or lifetime data, although the classical two-parameter Weibull distribution is limited to positive data and monotone failure rate. The parameters of the Weibull model are commonly obtained by maximum likelihood estimation; however, it is well-known that this estimator is not robust when dealing with contaminated data. A new robust procedure is introduced to fit a Weibull model by using L2 distance, i.e. integrated square distance, of the Weibull probability density function. The Weibull model is augmented with a weight parameter to robustly deal with contaminated data. Results comparing a maximum likelihood estimator with an L2 estimator are given in this article, based on both simulated and real data sets. It is shown that this new L2 parametric estimation method is more robust and does a better job than maximum likelihood in the newly proposed Weibull model when data are contaminated. The same preference for L2 distance criterion and the new Weibull model also happens for right-censored data with contamination. PMID:23888090
Fitting of Parametric Building Models to Oblique Aerial Images
NASA Astrophysics Data System (ADS)
Panday, U. S.; Gerke, M.
2011-09-01
In literature and in photogrammetric workstations many approaches and systems to automatically reconstruct buildings from remote sensing data are described and available. Those building models are being used for instance in city modeling or in cadastre context. If a roof overhang is present, the building walls cannot be estimated correctly from nadir-view aerial images or airborne laser scanning (ALS) data. This leads to inconsistent building outlines, which has a negative influence on visual impression, but more seriously also represents a wrong legal boundary in the cadaster. Oblique aerial images as opposed to nadir-view images reveal greater detail, enabling to see different views of an object taken from different directions. Building walls are visible from oblique images directly and those images are used for automated roof overhang estimation in this research. A fitting algorithm is employed to find roof parameters of simple buildings. It uses a least squares algorithm to fit projected wire frames to their corresponding edge lines extracted from the images. Self-occlusion is detected based on intersection result of viewing ray and the planes formed by the building whereas occlusion from other objects is detected using an ALS point cloud. Overhang and ground height are obtained by sweeping vertical and horizontal planes respectively. Experimental results are verified with high resolution ortho-images, field survey, and ALS data. Planimetric accuracy of 1cm mean and 5cm standard deviation was obtained, while buildings' orientation were accurate to mean of 0.23° and standard deviation of 0.96° with ortho-image. Overhang parameters were aligned to approximately 10cm with field survey. The ground and roof heights were accurate to mean of - 9cm and 8cm with standard deviations of 16cm and 8cm with ALS respectively. The developed approach reconstructs 3D building models well in cases of sufficient texture. More images should be acquired for completeness of
Using R^2 to compare least-squares fit models: When it must fail
Technology Transfer Automated Retrieval System (TEKTRAN)
R^2 can be used correctly to select from among competing least-squares fit models when the data are fitted in common form and with common weighting. However, then R^2 comparisons become equivalent to comparisons of the estimated fit variance s^2 in unweighted fitting, or of the reduced chi-square in...
A Newtonian Model of the Hydrogen Atom
NASA Astrophysics Data System (ADS)
Espinosa, James; Woodyard, James
2010-03-01
Classical physics was deemed useless in atomic physics in the early 1900's by the vast majority of the physics community. There were multiple problems that were believed to be insoluble, such as blackbody radiation and the photoelectric and Compton effects. Another outstanding problem had been the explanation of atomic spectra. By the 1920's, a very powerful theory called quantum mechanics was created which explained all atomic experiments. Nevertheless, a few physicists, most notably Albert Einstein, rejected this theory on the grounds that it did not give a complete description of the microscopic world. Another more radical view held by Walter Ritz is that Newtonian physics is applicable to all of atomic physics. Over the last couple of years, we have presented classical explanations of many of the ``insoluble'' problems given by textbooks. We will present a model of the hydrogen atom that stays within the framework of Newton. Using only the assumption that the stable building blocks of matter are the electron, positron, and neutrino, we will deduce the following results from our model: orbital stability, line spectra, and scattering cross sections for electrons and protons. We will also qualitatively demonstrate how to explain the lifetime of excited states.
Simulations of Statistical Model Fits to RHIC Data
NASA Astrophysics Data System (ADS)
Llope, W. J.
2013-04-01
The application of statistical model fits to experimentally measured particle multiplicity ratios allows inferences of the average values of temperatures, T, baryochemical potentials, μB, and other quantities at chemical freeze-out. The location of the boundary between the hadronic and partonic regions in the (μB,T) phase diagram, and the possible existence of a critical point, remains largely speculative. The search for a critical point using the moments of the particle multiplicity distributions in tightly centrality constrained event samples makes the tacit assumption that the variances in the (μB,T) values in these samples is sufficiently small to tightly localize the events in the phase diagram. This and other aspects were explored in simulations by coupling the UrQMD transport model to the statistical model code Thermus. The phase diagram trajectories of individual events versus the time in fm/c was calculated versus the centrality and beam energy. The variances of the (μB,T) values at freeze-out, even in narrow centrality bins, are seen to be relatively large. This suggests that a new way to constrain the events on the phase diagram may lead to more sensitive searches for the possible critical point.
A Comprehensive X-Ray Absorption Model for Atomic Oxygen
NASA Technical Reports Server (NTRS)
Gorczyca, T. W.; Bautista, M. A.; Hasoglu, M. F.; Garcia, J.; Gatuzz, E.; Kaastra, J. S.; Kallman, T. R.; Manson, S. T.; Mendoza, C.; Raassen, A. J. J.; de Vries, C. P.; Zatsarinny, O.
2013-01-01
An analytical formula is developed to accurately represent the photoabsorption cross section of atomic Oxygen for all energies of interest in X-ray spectral modeling. In the vicinity of the K edge, a Rydberg series expression is used to fit R-matrix results, including important orbital relaxation effects, that accurately predict the absorption oscillator strengths below threshold and merge consistently and continuously to the above-threshold cross section. Further, minor adjustments are made to the threshold energies in order to reliably align the atomic Rydberg resonances after consideration of both experimental and observed line positions. At energies far below or above the K-edge region, the formulation is based on both outer- and inner-shell direct photoionization, including significant shake-up and shake-off processes that result in photoionization-excitation and double-photoionization contributions to the total cross section. The ultimate purpose for developing a definitive model for oxygen absorption is to resolve standing discrepancies between the astronomically observed and laboratory-measured line positions, and between the inferred atomic and molecular oxygen abundances in the interstellar medium from XSTAR and SPEX spectral models.
Melbourne, Andrew; Toussaint, Nicolas; Owen, David; Simpson, Ivor; Anthopoulos, Thanasis; De Vita, Enrico; Atkinson, David; Ourselin, Sebastien
2016-07-01
Multi-modal, multi-parametric Magnetic Resonance (MR) Imaging is becoming an increasingly sophisticated tool for neuroimaging. The relationships between parameters estimated from different individual MR modalities have the potential to transform our understanding of brain function, structure, development and disease. This article describes a new software package for such multi-contrast Magnetic Resonance Imaging that provides a unified model-fitting framework. We describe model-fitting functionality for Arterial Spin Labeled MRI, T1 Relaxometry, T2 relaxometry and Diffusion Weighted imaging, providing command line documentation to generate the figures in the manuscript. Software and data (using the nifti file format) used in this article are simultaneously provided for download. We also present some extended applications of the joint model fitting framework applied to diffusion weighted imaging and T2 relaxometry, in order to both improve parameter estimation in these models and generate new parameters that link different MR modalities. NiftyFit is intended as a clear and open-source educational release so that the user may adapt and develop their own functionality as they require. PMID:26972806
Atomic Data Applications for Supernova Modeling
NASA Astrophysics Data System (ADS)
Fontes, Christopher J.
2013-06-01
The modeling of supernovae (SNe) incorporates a variety of disciplines, including hydrodynamics, radiation transport, nuclear physics and atomic physics. These efforts require numerical simulation of the final stages of a star's life, the supernova explosion phase, and the radiation that is subsequently emitted by the supernova remnant, which can occur over a time span of tens of thousands of years. While there are several different types of SNe, they all emit radiation in some form. The measurement and interpretation of these spectra provide important information about the structure of the exploding star and the supernova engine. In this talk, the role of atomic data is highlighted as iit pertains to the modeling of supernova spectra. Recent applications [1,2] involve the Los Alamos OPLIB opacity database, which has been used to provide atomic opacities for modeling supernova plasmas under local thermodynamic equilibrium (LTE) conditions. Ongoing work includes the application of atomic data generated by the Los Alamos suite of atomic physics codes under more complicated, non-LTE conditions [3]. As a specific, recent example, a portion of the x-ray spectrum produced by Tycho's supernova remnant (SN 1572) will be discussed [4]. [1] C.L. Fryer et al, Astrophys. J. 707, 193 (2009). [2] C.L. Fryer et al, Astrophys. J. 725, 296 (2009). [3] C.J. Fontes et al, Conference Proceedings for ICPEAC XXVII, J. of Phys: Conf. Series 388, 012022 (2012). [4] K.A. Eriksen et al, Presentation at the 2012 AAS Meeting (Austin, TX). (This work was performed under the auspices of the U.S. Department of Energy by Los Alamos National Laboratory under Contract No. DE-AC52-06NA25396.)
ERIC Educational Resources Information Center
Zhang, Wei
2008-01-01
A major issue in the utilization of covariance structure analysis is model fit evaluation. Recent years have witnessed increasing interest in various test statistics and so-called fit indexes, most of which are actually based on or closely related to F[subscript 0], a measure of model fit in the population. This study aims to provide a systematic…
Performance of the Generalized S-X[squared] Item Fit Index for the Graded Response Model
ERIC Educational Resources Information Center
Kang, Taehoon; Chen, Troy T.
2011-01-01
The utility of Orlando and Thissen's ("2000", "2003") S-X[squared] fit index was extended to the model-fit analysis of the graded response model (GRM). The performance of a modified S-X[squared] in assessing item-fit of the GRM was investigated in light of empirical Type I error rates and power with a simulation study having various conditions…
Model-independent fit to Planck and BICEP2 data
NASA Astrophysics Data System (ADS)
Barranco, Laura; Boubekeur, Lotfi; Mena, Olga
2014-09-01
Inflation is the leading theory to describe elegantly the initial conditions that led to structure formation in our Universe. In this paper, we present a novel phenomenological fit to the Planck, WMAP polarization (WP) and the BICEP2 data sets using an alternative parametrization. Instead of starting from inflationary potentials and computing the inflationary observables, we use a phenomenological parametrization due to Mukhanov, describing inflation by an effective equation of state, in terms of the number of e-folds and two phenomenological parameters α and β. Within such a parametrization, which captures the different inflationary models in a model-independent way, the values of the scalar spectral index ns, its running and the tensor-to-scalar ratio r are predicted, given a set of parameters (α ,β). We perform a Markov Chain Monte Carlo analysis of these parameters, and we show that the combined analysis of Planck and WP data favors the Starobinsky and Higgs inflation scenarios. Assuming that the BICEP2 signal is not entirely due to foregrounds, the addition of this last data set prefers instead the ϕ2 chaotic models. The constraint we get from Planck and WP data alone on the derived tensor-to-scalar ratio is r <0.18 at 95% C.L., value which is consistent with the one quoted from the BICEP2 Collaboration analysis, r =0.16-0.05+0-06, after foreground subtraction. This is not necessarily at odds with the 2σ tension found between Planck and BICEP2 measurements when analyzing data in terms of the usual ns and r parameters, given that the parametrization used here, for the preferred value ns≃0.96, allows only for a restricted parameter space in the usual (ns,r) plane.
Optical analogs of model atoms in fields
Milonni, P.W.
1991-05-02
The equivalence of the paraxial wave equation to a time-dependent Schroedinger equation is exploited to construct optical analogs of model atoms in monochromatic fields. The approximation of geometrical optics provides the analog of the corresponding classical mechanics. Optical analogs of Rabi oscillations, photoionization, stabilization, and the Kramers-Henneberger transformation are discussed. One possibility for experimental realization of such optical analogs is proposed. These analogs may be useful for studies of quantum chaos'' when the ray trajectories are chaotic. 9 refs.
A quantitative confidence signal detection model: 1. Fitting psychometric functions.
Yi, Yongwoo; Merfeld, Daniel M
2016-04-01
Perceptual thresholds are commonly assayed in the laboratory and clinic. When precision and accuracy are required, thresholds are quantified by fitting a psychometric function to forced-choice data. The primary shortcoming of this approach is that it typically requires 100 trials or more to yield accurate (i.e., small bias) and precise (i.e., small variance) psychometric parameter estimates. We show that confidence probability judgments combined with a model of confidence can yield psychometric parameter estimates that are markedly more precise and/or markedly more efficient than conventional methods. Specifically, both human data and simulations show that including confidence probability judgments for just 20 trials can yield psychometric parameter estimates that match the precision of those obtained from 100 trials using conventional analyses. Such an efficiency advantage would be especially beneficial for tasks (e.g., taste, smell, and vestibular assays) that require more than a few seconds for each trial, but this potential benefit could accrue for many other tasks. PMID:26763777
A Green's function quantum average atom model
Starrett, Charles Edward
2015-05-21
A quantum average atom model is reformulated using Green's functions. This allows integrals along the real energy axis to be deformed into the complex plane. The advantage being that sharp features such as resonances and bound states are broadened by a Lorentzian with a half-width chosen for numerical convenience. An implementation of this method therefore avoids numerically challenging resonance tracking and the search for weakly bound states, without changing the physical content or results of the model. A straightforward implementation results in up to a factor of 5 speed-up relative to an optimized orbital based code.
Atom-Role-Based Access Control Model
NASA Astrophysics Data System (ADS)
Cai, Weihong; Huang, Richeng; Hou, Xiaoli; Wei, Gang; Xiao, Shui; Chen, Yindong
Role-based access control (RBAC) model has been widely recognized as an efficient access control model and becomes a hot research topic of information security at present. However, in the large-scale enterprise application environments, the traditional RBAC model based on the role hierarchy has the following deficiencies: Firstly, it is unable to reflect the role relationships in complicated cases effectively, which does not accord with practical applications. Secondly, the senior role unconditionally inherits all permissions of the junior role, thus if a user is under the supervisor role, he may accumulate all permissions, and this easily causes the abuse of permission and violates the least privilege principle, which is one of the main security principles. To deal with these problems, we, after analyzing permission types and role relationships, proposed the concept of atom role and built an atom-role-based access control model, called ATRBAC, by dividing the permission set of each regular role based on inheritance path relationships. Through the application-specific analysis, this model can well meet the access control requirements.
An Application of M[subscript 2] Statistic to Evaluate the Fit of Cognitive Diagnostic Models
ERIC Educational Resources Information Center
Liu, Yanlou; Tian, Wei; Xin, Tao
2016-01-01
The fit of cognitive diagnostic models (CDMs) to response data needs to be evaluated, since CDMs might yield misleading results when they do not fit the data well. Limited-information statistic M[subscript 2] and the associated root mean square error of approximation (RMSEA[subscript 2]) in item factor analysis were extended to evaluate the fit of…
Comparing the Fit of Item Response Theory and Factor Analysis Models
ERIC Educational Resources Information Center
Maydeu-Olivares, Alberto; Cai, Li; Hernandez, Adolfo
2011-01-01
Linear factor analysis (FA) models can be reliably tested using test statistics based on residual covariances. We show that the same statistics can be used to reliably test the fit of item response theory (IRT) models for ordinal data (under some conditions). Hence, the fit of an FA model and of an IRT model to the same data set can now be…
Convergence, Admissibility, and Fit of Alternative Confirmatory Factor Analysis Models for MTMM Data
ERIC Educational Resources Information Center
Lance, Charles E.; Fan, Yi
2016-01-01
We compared six different analytic models for multitrait-multimethod (MTMM) data in terms of convergence, admissibility, and model fit to 258 samples of previously reported data. Two well-known models, the correlated trait-correlated method (CTCM) and the correlated trait-correlated uniqueness (CTCU) models, were fit for reference purposes in…
ERIC Educational Resources Information Center
Finch, W. Holmes; Finch, Maria E. Hernandez
2016-01-01
Researchers and data analysts are sometimes faced with the problem of very small samples, where the number of variables approaches or exceeds the overall sample size; i.e. high dimensional data. In such cases, standard statistical models such as regression or analysis of variance cannot be used, either because the resulting parameter estimates…
NASA Technical Reports Server (NTRS)
Sokalski, W. A.; Shibata, M.; Ornstein, R. L.; Rein, R.
1992-01-01
The quality of several atomic charge models based on different definitions has been analyzed using cumulative atomic multipole moments (CAMM). This formalism can generate higher atomic moments starting from any atomic charges, while preserving the corresponding molecular moments. The atomic charge contribution to the higher molecular moments, as well as to the electrostatic potentials, has been examined for CO and HCN molecules at several different levels of theory. The results clearly show that the electrostatic potential obtained from CAMM expansion is convergent up to R-5 term for all atomic charge models used. This illustrates that higher atomic moments can be used to supplement any atomic charge model to obtain more accurate description of electrostatic properties.
A comprehensive X-ray absorption model for atomic oxygen
Gorczyca, T. W.; Bautista, M. A.; Mendoza, C.; Hasoglu, M. F.; García, J.; Gatuzz, E.; Kaastra, J. S.; Raassen, A. J. J.; De Vries, C. P.; Kallman, T. R.; Manson, S. T.; Zatsarinny, O.
2013-12-10
An analytical formula is developed to accurately represent the photoabsorption cross section of O I for all energies of interest in X-ray spectral modeling. In the vicinity of the K edge, a Rydberg series expression is used to fit R-matrix results, including important orbital relaxation effects, that accurately predict the absorption oscillator strengths below threshold and merge consistently and continuously to the above-threshold cross section. Further, minor adjustments are made to the threshold energies in order to reliably align the atomic Rydberg resonances after consideration of both experimental and observed line positions. At energies far below or above the K-edge region, the formulation is based on both outer- and inner-shell direct photoionization, including significant shake-up and shake-off processes that result in photoionization-excitation and double-photoionization contributions to the total cross section. The ultimate purpose for developing a definitive model for oxygen absorption is to resolve standing discrepancies between the astronomically observed and laboratory-measured line positions, and between the inferred atomic and molecular oxygen abundances in the interstellar medium from XSTAR and SPEX spectral models.
Making It Visual: Creating a Model of the Atom
ERIC Educational Resources Information Center
Pringle, Rose M.
2004-01-01
This article describes a lesson in which students construct Bohr's planetary model of the atom. Niels Bohr's atomic model provides a framework for discussing with middle and high school students the historical development of our understanding of the structure of the atom. The model constructed in this activity will enable students to visualize the…
Derevyanko, Georgy; Grudinin, Sergei
2014-08-01
HermiteFit, a novel algorithm for fitting a protein structure into a low-resolution electron-density map, is presented. The algorithm accelerates the rotation of the Fourier image of the electron density by using three-dimensional orthogonal Hermite functions. As part of the new method, an algorithm for the rotation of the density in the Hermite basis and an algorithm for the conversion of the expansion coefficients into the Fourier basis are presented. HermiteFit was implemented using the cross-correlation or the Laplacian-filtered cross-correlation as the fitting criterion. It is demonstrated that in the Hermite basis the Laplacian filter has a particularly simple form. To assess the quality of density encoding in the Hermite basis, an analytical way of computing the crystallographic R factor is presented. Finally, the algorithm is validated using two examples and its efficiency is compared with two widely used fitting methods, ADP_EM and colores from the Situs package. HermiteFit will be made available at http://nano-d.inrialpes.fr/software/HermiteFit or upon request from the authors. PMID:25084327
Computer Model Of Fragmentation Of Atomic Nuclei
NASA Technical Reports Server (NTRS)
Wilson, John W.; Townsend, Lawrence W.; Tripathi, Ram K.; Norbury, John W.; KHAN FERDOUS; Badavi, Francis F.
1995-01-01
High Charge and Energy Semiempirical Nuclear Fragmentation Model (HZEFRG1) computer program developed to be computationally efficient, user-friendly, physics-based program for generating data bases on fragmentation of atomic nuclei. Data bases generated used in calculations pertaining to such radiation-transport applications as shielding against radiation in outer space, radiation dosimetry in outer space, cancer therapy in laboratories with beams of heavy ions, and simulation studies for designing detectors for experiments in nuclear physics. Provides cross sections for production of individual elements and isotopes in breakups of high-energy heavy ions by combined nuclear and Coulomb fields of interacting nuclei. Written in ANSI FORTRAN 77.
YUP.SCX: Coaxing Atomic Models into Medium Resolution Electron Density Maps
Tan, Robert K.-Z.; Devkota, Batsal; Harvey, Stephen C.
2008-01-01
The structures of large macromolecular complexes in different functional states can be determined by cryo-electron microscopy, which yields electron density maps of low to intermediate resolutions. The maps can be combined with high-resolution atomic structures of components of the complex, to produce a model for the complex that is more accurate than the formal resolution of the map. To this end, methods have been developed to dock atomic models into density maps rigidly or flexibly, and to refine a docked model so as to optimize the fit of the atomic model into the map. We have developed a new refinement method called YUP.SCX. The electron density map is converted into a component of the potential energy function to which terms for stereochemical restraints and volume exclusion are added. The potential energy function is then minimized (using simulated annealing) to yield a stereochemically-restrained atomic structure that fits into the electron density map optimally. We used this procedure to construct an atomic model of the 70S ribosome in the pre-accommodation state. Although some atoms are displaced by as much as 33 Å, they divide themselves into nearly rigid fragments along natural boundaries with smooth transitions between the fragments. PMID:18572416
The Search for "Optimal" Cutoff Properties: Fit Index Criteria in Structural Equation Modeling
ERIC Educational Resources Information Center
Sivo, Stephen A.; Xitao, Fan; Witta, E. Lea; Willse, John T.
2006-01-01
This study is a partial replication of L. Hu and P. M. Bentler's (1999) fit criteria work. The purpose of this study was twofold: (a) to determine whether cut-off values vary according to which model is the true population model for a dataset and (b) to identify which of 13 fit indexes behave optimally by retaining all of the correct models while…
ERIC Educational Resources Information Center
Dyehouse, Melissa A.
2009-01-01
This study compared the model-data fit of a parametric item response theory (PIRT) model to a nonparametric item response theory (NIRT) model to determine the best-fitting model for use with ordinal-level alternate assessment ratings. The PIRT Generalized Graded Unfolding Model (GGUM) was compared to the NIRT Mokken model. Chi-square statistics…
Multiplex networks with intrinsic fitness: Modeling the merit-fame interplay via latent layers
NASA Astrophysics Data System (ADS)
Fotouhi, Babak; Momeni, Naghmeh
2015-11-01
We consider the problem of growing multiplex networks with intrinsic fitness and inter-layer coupling. The model comprises two layers; one that incorporates fitness and another in which attachments are preferential. In the first layer, attachment probabilities are proportional to fitness values, and in the second layer, proportional to the sum of degrees in both layers. We provide analytical closed-form solutions for the joint distributions of fitness and degrees. We also derive closed-form expressions for the expected value of the degree as a function of fitness. The model alleviates two shortcomings that are present in the current models of growing multiplex networks: homogeneity of connections, and homogeneity of fitness. In this paper, we posit and analyze a growth model that is heterogeneous in both senses.
Refinement of atomic models in high resolution EM reconstructions using Flex-EM and local assessment
Joseph, Agnel Praveen; Malhotra, Sony; Burnley, Tom; Wood, Chris; Clare, Daniel K.; Winn, Martyn; Topf, Maya
2016-01-01
As the resolutions of Three Dimensional Electron Microscopic reconstructions of biological macromolecules are being improved, there is a need for better fitting and refinement methods at high resolutions and robust approaches for model assessment. Flex-EM/MODELLER has been used for flexible fitting of atomic models in intermediate-to-low resolution density maps of different biological systems. Here, we demonstrate the suitability of the method to successfully refine structures at higher resolutions (2.5–4.5 Å) using both simulated and experimental data, including a newly processed map of Apo-GroEL. A hierarchical refinement protocol was adopted where the rigid body definitions are relaxed and atom displacement steps are reduced progressively at successive stages of refinement. For the assessment of local fit, we used the SMOC (segment-based Manders’ overlap coefficient) score, while the model quality was checked using the Qmean score. Comparison of SMOC profiles at different stages of refinement helped in detecting regions that are poorly fitted. We also show how initial model errors can have significant impact on the goodness-of-fit. Finally, we discuss the implementation of Flex-EM in the CCP-EM software suite. PMID:26988127
Joseph, Agnel Praveen; Malhotra, Sony; Burnley, Tom; Wood, Chris; Clare, Daniel K; Winn, Martyn; Topf, Maya
2016-05-01
As the resolutions of Three Dimensional Electron Microscopic reconstructions of biological macromolecules are being improved, there is a need for better fitting and refinement methods at high resolutions and robust approaches for model assessment. Flex-EM/MODELLER has been used for flexible fitting of atomic models in intermediate-to-low resolution density maps of different biological systems. Here, we demonstrate the suitability of the method to successfully refine structures at higher resolutions (2.5-4.5Å) using both simulated and experimental data, including a newly processed map of Apo-GroEL. A hierarchical refinement protocol was adopted where the rigid body definitions are relaxed and atom displacement steps are reduced progressively at successive stages of refinement. For the assessment of local fit, we used the SMOC (segment-based Manders' overlap coefficient) score, while the model quality was checked using the Qmean score. Comparison of SMOC profiles at different stages of refinement helped in detecting regions that are poorly fitted. We also show how initial model errors can have significant impact on the goodness-of-fit. Finally, we discuss the implementation of Flex-EM in the CCP-EM software suite. PMID:26988127
Model Fitting for Predicted Precipitation in Darwin: Some Issues with Model Choice
ERIC Educational Resources Information Center
Farmer, Jim
2010-01-01
In Volume 23(2) of the "Australian Senior Mathematics Journal," Boncek and Harden present an exercise in fitting a Markov chain model to rainfall data for Darwin Airport (Boncek & Harden, 2009). Days are subdivided into those with precipitation and precipitation-free days. The author abbreviates these labels to wet days and dry days. It is…
Atomic Models for Motional Stark Effects Diagnostics
Gu, M F; Holcomb, C; Jayakuma, J; Allen, S; Pablant, N A; Burrell, K
2007-07-26
We present detailed atomic physics models for motional Stark effects (MSE) diagnostic on magnetic fusion devices. Excitation and ionization cross sections of the hydrogen or deuterium beam traveling in a magnetic field in collisions with electrons, ions, and neutral gas are calculated in the first Born approximation. The density matrices and polarization states of individual Stark-Zeeman components of the Balmer {alpha} line are obtained for both beam into plasma and beam into gas models. A detailed comparison of the model calculations and the MSE polarimetry and spectral intensity measurements obtained at the DIII-D tokamak is carried out. Although our beam into gas models provide a qualitative explanation for the larger {pi}/{sigma} intensity ratios and represent significant improvements over the statistical population models, empirical adjustment factors ranging from 1.0-2.0 must still be applied to individual line intensities to bring the calculations into full agreement with the observations. Nevertheless, we demonstrate that beam into gas measurements can be used successfully as calibration procedures for measuring the magnetic pitch angle through {pi}/{sigma} intensity ratios. The analyses of the filter-scan polarization spectra from the DIII-D MSE polarimetry system indicate unknown channel and time dependent light contaminations in the beam into gas measurements. Such contaminations may be the main reason for the failure of beam into gas calibration on MSE polarimetry systems.
Why Should We Assess the Goodness-of-Fit of IRT Models?
ERIC Educational Resources Information Center
Maydeu-Olivares, Alberto
2013-01-01
In this rejoinder, Maydeu-Olivares states that, in item response theory (IRT) measurement applications, the application of goodness-of-fit (GOF) methods informs researchers of the discrepancy between the model and the data being fitted (the room for improvement). By routinely reporting the GOF of IRT models, together with the substantive results…
Fitting the Rasch Model to Account for Variation in Item Discrimination
ERIC Educational Resources Information Center
Weitzman, R. A.
2009-01-01
Building on the Kelley and Gulliksen versions of classical test theory, this article shows that a logistic model having only a single item parameter can account for varying item discrimination, as well as difficulty, by using item-test correlations to adjust incorrect-correct (0-1) item responses prior to an initial model fit. The fit occurs…
Performance of the Generalized S-X[Superscript 2] Item Fit Index for Polytomous IRT Models
ERIC Educational Resources Information Center
Kang, Taehoon; Chen, Troy T.
2008-01-01
Orlando and Thissen's S-X[superscript 2] item fit index has performed better than traditional item fit statistics such as Yen' s Q[subscript 1] and McKinley and Mill' s G[superscript 2] for dichotomous item response theory (IRT) models. This study extends the utility of S-X[superscript 2] to polytomous IRT models, including the generalized partial…
Residuals and the Residual-Based Statistic for Testing Goodness of Fit of Structural Equation Models
ERIC Educational Resources Information Center
Foldnes, Njal; Foss, Tron; Olsson, Ulf Henning
2012-01-01
The residuals obtained from fitting a structural equation model are crucial ingredients in obtaining chi-square goodness-of-fit statistics for the model. The authors present a didactic discussion of the residuals, obtaining a geometrical interpretation by recognizing the residuals as the result of oblique projections. This sheds light on the…
ERIC Educational Resources Information Center
Bauer, Daniel J.; Sterba, Sonya K.
2011-01-01
Previous research has compared methods of estimation for fitting multilevel models to binary data, but there are reasons to believe that the results will not always generalize to the ordinal case. This article thus evaluates (a) whether and when fitting multilevel linear models to ordinal outcome data is justified and (b) which estimator to employ…
TRANSIT MODEL FITTING IN THE KEPLER SCIENCE OPERATIONS CENTER PIPELINE: NEW FEATURES AND PERFORMANCE
NASA Astrophysics Data System (ADS)
Li, Jie; Burke, C. J.; Jenkins, J. M.; Quintana, E. V.; Rowe, J. F.; Seader, S. E.; Tenenbaum, P.; Twicken, J. D.
2013-10-01
We describe new transit model fitting features and performance of the latest release (9.1, July 2013) of the Kepler Science Operations Center (SOC) Pipeline. The targets for which a Threshold Crossing Event (TCE) is generated in the Transiting Planet Search (TPS) component of the pipeline are subsequently processed in the Data Validation (DV) component. Transit model parameters are fitted in DV to transit-like signatures in the light curves of the targets with TCEs. The transit model fitting results are used in diagnostic tests in DV, which help to validate planet candidates and identify false positive detections. The standard transit model includes five fit parameters: transit epoch time (i.e. central time of first transit), orbital period, impact parameter, ratio of planet radius to star radius and ratio of semi-major axis to star radius. Light curves for many targets do not contain enough information to uniquely determine the impact parameter, which results in poor convergence performance of the fitter. In the latest release of the Kepler SOC pipeline, a reduced parameter fit is included in DV: the impact parameter is set to a fixed value and the four remaining parameters are fitted. The standard transit model fit is implemented after a series of reduced parameter fits in which the impact parameter is varied between 0 and 1. Initial values for the standard transit model fit parameters are determined by the reduced parameter fit with the minimum chi-square metric. With reduced parameter fits, the robustness of the transit model fit is improved significantly. Diagnostic plots of the chi-square metrics and reduced parameter fit results illustrate how the fitted parameters vary as a function of impact parameter. Essentially, a family of transiting planet characteristics is determined in DV for each Pipeline TCE. Transit model fitting performance of release 9.1 of the Kepler SOC pipeline is demonstrated with the results of the processing of 16 quarters of flight data
Operation of the computer model for microenvironment atomic oxygen exposure
NASA Technical Reports Server (NTRS)
Bourassa, R. J.; Gillis, J. R.; Gruenbaum, P. E.
1995-01-01
A computer model for microenvironment atomic oxygen exposure has been developed to extend atomic oxygen modeling capability to include shadowing and reflections. The model uses average exposure conditions established by the direct exposure model and extends the application of these conditions to treat surfaces of arbitrary shape and orientation.
NASA Astrophysics Data System (ADS)
Mead, A. J.; Peacock, J. A.; Heymans, C.; Joudaki, S.; Heavens, A. F.
2015-12-01
We present an optimized variant of the halo model, designed to produce accurate matter power spectra well into the non-linear regime for a wide range of cosmological models. To do this, we introduce physically motivated free parameters into the halo-model formalism and fit these to data from high-resolution N-body simulations. For a variety of Λ cold dark matter (ΛCDM) and wCDM models, the halo-model power is accurate to ≃ 5 per cent for k ≤ 10h Mpc-1 and z ≤ 2. An advantage of our new halo model is that it can be adapted to account for the effects of baryonic feedback on the power spectrum. We demonstrate this by fitting the halo model to power spectra from the OWLS (OverWhelmingly Large Simulations) hydrodynamical simulation suite via parameters that govern halo internal structure. We are able to fit all feedback models investigated at the 5 per cent level using only two free parameters, and we place limits on the range of these halo parameters for feedback models investigated by the OWLS simulations. Accurate predictions to high k are vital for weak-lensing surveys, and these halo parameters could be considered nuisance parameters to marginalize over in future analyses to mitigate uncertainty regarding the details of feedback. Finally, we investigate how lensing observables predicted by our model compare to those from simulations and from HALOFIT for a range of k-cuts and feedback models and quantify the angular scales at which these effects become important. Code to calculate power spectra from the model presented in this paper can be found at https://github.com/alexander-mead/hmcode.
Assessing Fit of Cognitive Diagnostic Models: A Case Study
ERIC Educational Resources Information Center
Sinharay, Sandip; Almond, Russell G.
2007-01-01
A cognitive diagnostic model uses information from educational experts to describe the relationships between item performances and posited proficiencies. When the cognitive relationships can be described using a fully Bayesian model, Bayesian model checking procedures become available. Checking models tied to cognitive theory of the domains…
Atomic Oscillator Strengths for Stellar Atmosphere Modeling
NASA Astrophysics Data System (ADS)
Ruffoni, Matthew; Pickering, Juliet C.
2015-08-01
In order to correctly model stellar atmospheres, fundamental atomic data must be available to describe atomic lines observed in their spectra. Accurate, laboratory-measured oscillator strengths (f-values) for Fe peak elements in neutral or low-ionisation states are particularly important for determining chemical abundances.However, advances in astronomical spectroscopy in recent decades have outpaced those in laboratory astrophysics, with the latter frequently being overlooked at the planning stages of new projects. As a result, numerous big-budget astronomy projects have been, and continue to be hindered by a lack of suitable, accurately-measured reference data to permit the analysis of expensive astronomical spectra; a problem only likely to worsen in the coming decades as spectrographs at new facilities increasingly move to infrared wavelengths.At Imperial College London - and in collaboration with NIST, Wisconsin University and Lund University - we have been working with the astronomy community in an effort to provide new accurately-measured f-values for a range of projects. In particular, we have been working closely with the Gaia-ESO (GES) and SDSS-III/APOGEE surveys, both of which have discovered that many lines that would make ideal candidates for inclusion in their analyses have poorly defined f-values, or are simply absent from the database. Using high-resolution Fourier transform spectroscopy (R ~ 2,000,000) to provide atomic branching fractions, and combining these with level lifetimes measured with laser induced fluorescence, we have provided new laboratory-measured f-values for a range of Fe-peak elements, most recently including Fe I, Fe II, and V I. For strong, unblended lines, uncertainties are as low as ±0.02 dex.In this presentation, I will describe how experimental f-values are obtained in the laboratory and present our recent work for GES and APOGEE. In particular, I will also discuss the strengths and limitations of current laboratory
Project Physics Text 5, Models of the Atom.
ERIC Educational Resources Information Center
Harvard Univ., Cambridge, MA. Harvard Project Physics.
Basic atomic theories are presented in this fifth unit of the Project Physics text for use by senior high students. Chemical basis of atomic models in the early years of the 18th Century is discussed n connection with Dalton's theory, atomic properties, and periodic tables. The discovery of electrons is described by using cathode rays, Millikan's…
Moment-Based Probability Modeling and Extreme Response Estimation, The FITS Routine Version 1.2
MANUEL,LANCE; KASHEF,TINA; WINTERSTEIN,STEVEN R.
1999-11-01
This report documents the use of the FITS routine, which provides automated fits of various analytical, commonly used probability models from input data. It is intended to complement the previously distributed FITTING routine documented in RMS Report 14 (Winterstein et al., 1994), which implements relatively complex four-moment distribution models whose parameters are fit with numerical optimization routines. Although these four-moment fits can be quite useful and faithful to the observed data, their complexity can make them difficult to automate within standard fitting algorithms. In contrast, FITS provides more robust (lower moment) fits of simpler, more conventional distribution forms. For each database of interest, the routine estimates the distribution of annual maximum response based on the data values and the duration, T, over which they were recorded. To focus on the upper tails of interest, the user can also supply an arbitrary lower-bound threshold, {chi}{sub low}, above which a shifted distribution model--exponential or Weibull--is fit.
Mac, Amy; Rhodes, Gillian; Webster, Michael A.
2015-01-01
Recently, we proposed that the aftereffects of adapting to facial age are consistent with a renormalization of the perceived age (e.g., so that after adapting to a younger or older age, all ages appear slightly older or younger, respectively). This conclusion has been challenged by arguing that the aftereffects can also be accounted for by an alternative model based on repulsion (in which facial ages above or below the adapting age are biased away from the adaptor). However, we show here that this challenge was based on allowing the fitted functions to take on values which are implausible and incompatible across the different adapting conditions. When the fits are constrained or interpreted in terms of standard assumptions about normalization and repulsion, then the two analyses both agree in pointing to a pattern of renormalization in age aftereffects. PMID:27551353
2014-01-01
Background Striking a balance between the degree of model complexity and parameter identifiability, while still producing biologically feasible simulations using modelling is a major challenge in computational biology. While these two elements of model development are closely coupled, parameter fitting from measured data and analysis of model mechanisms have traditionally been performed separately and sequentially. This process produces potential mismatches between model and data complexities that can compromise the ability of computational frameworks to reveal mechanistic insights or predict new behaviour. In this study we address this issue by presenting a generic framework for combined model parameterisation, comparison of model alternatives and analysis of model mechanisms. Results The presented methodology is based on a combination of multivariate metamodelling (statistical approximation of the input–output relationships of deterministic models) and a systematic zooming into biologically feasible regions of the parameter space by iterative generation of new experimental designs and look-up of simulations in the proximity of the measured data. The parameter fitting pipeline includes an implicit sensitivity analysis and analysis of parameter identifiability, making it suitable for testing hypotheses for model reduction. Using this approach, under-constrained model parameters, as well as the coupling between parameters within the model are identified. The methodology is demonstrated by refitting the parameters of a published model of cardiac cellular mechanics using a combination of measured data and synthetic data from an alternative model of the same system. Using this approach, reduced models with simplified expressions for the tropomyosin/crossbridge kinetics were found by identification of model components that can be omitted without affecting the fit to the parameterising data. Our analysis revealed that model parameters could be constrained to a standard
An atomic model for neutral and singly ionized uranium
NASA Technical Reports Server (NTRS)
Maceda, E. L.; Miley, G. H.
1979-01-01
A model for the atomic levels above ground state in neutral, U(0), and singly ionized, U(+), uranium is described based on identified atomic transitions. Some 168 states in U(0) and 95 in U(+) are found. A total of 1581 atomic transitions are used to complete this process. Also discussed are the atomic inverse lifetimes and line widths for the radiative transitions as well as the electron collisional cross sections.
Using LISREL to Fit Nonlinear Latent Curve Models
ERIC Educational Resources Information Center
Blozis, Shelley A.; Harring, Jeffrey R.; Mels, Gerhard
2008-01-01
Latent curve models offer a flexible approach to the study of longitudinal data when the form of change in a response is nonlinear. This article considers such models that are conditionally linear with regard to the random coefficients at the 2nd level. This framework allows fixed parameters to enter a model linearly or nonlinearly, and random…
A simple model of group selection that cannot be analyzed with inclusive fitness.
van Veelen, Matthijs; Luo, Shishi; Simon, Burton
2014-11-01
A widespread claim in evolutionary theory is that every group selection model can be recast in terms of inclusive fitness. Although there are interesting classes of group selection models for which this is possible, we show that it is not true in general. With a simple set of group selection models, we show two distinct limitations that prevent recasting in terms of inclusive fitness. The first is a limitation across models. We show that if inclusive fitness is to always give the correct prediction, the definition of relatedness needs to change, continuously, along with changes in the parameters of the model. This results in infinitely many different definitions of relatedness - one for every parameter value - which strips relatedness of its meaning. The second limitation is across time. We show that one can find the trajectory for the group selection model by solving a partial differential equation, and that it is mathematically impossible to do this using inclusive fitness. PMID:25034338
A life-history model of human fitness indicators.
Sefcek, Jon A; Figueredo, Aurelio José
2010-01-01
Recent adaptationist accounts of human mental and physical health have reinvigorated the debate over the evolution of human intelligence. In the tradition of strong inference the current study was developed to determine whether either Miller's (1998, 2000a) Fitness Indicator Theory or Rushton's (1985, 2000) Differential-K Theory better accounts for general intelligence ("g") in an undergraduate university population (N=192). Owing to the lengthy administration time of the test materials, a newly developed 18-item short form of the Ravens Advanced Progressive Matrices (APM-18; Sefcek, Miller, and Figueredo 2007) was used. A significant, positive relationship between K and F (r = .31, p < .001) emerged. Contrary to predictions, no significant relationships were found between "g" and either K or F (r = -.09, p > or = .05 and r = .11, p > or = .05, respectively). Though generally contrary to both hypotheses, these results may be explained in relation to antagonistic pleiotropy and a potential failure to derive correct predictions for within-species comparisons directly from the results of between-species comparisons. PMID:20589987
Characterization of Titan 3-D acoustic pressure spectra by least-squares fit to theoretical model
NASA Astrophysics Data System (ADS)
Hartnett, E. B.; Carleen, E.
1980-01-01
A theoretical model for the acoustic spectra of undeflected rocket plumes is fitted to computed spectra of a Titan III-D at varying times after ignition, by a least-squares method. Tests for the goodness of the fit are made.
The Relation among Fit Indexes, Power, and Sample Size in Structural Equation Modeling
ERIC Educational Resources Information Center
Kim, Kevin H.
2005-01-01
The relation among fit indexes, power, and sample size in structural equation modeling is examined. The noncentrality parameter is required to compute power. The 2 existing methods of computing power have estimated the noncentrality parameter by specifying an alternative hypothesis or alternative fit. These methods cannot be implemented easily and…
ERIC Educational Resources Information Center
Lee, Young-Sun; Wollack, James A.; Douglas, Jeffrey
2009-01-01
The purpose of this study was to assess the model fit of a 2PL through comparison with the nonparametric item characteristic curve (ICC) estimation procedures. Results indicate that three nonparametric procedures implemented produced ICCs that are similar to that of the 2PL for items simulated to fit the 2PL. However for misfitting items,…
ERIC Educational Resources Information Center
Cai, Li; Lee, Taehun
2009-01-01
We apply the Supplemented EM algorithm (Meng & Rubin, 1991) to address a chronic problem with the "two-stage" fitting of covariance structure models in the presence of ignorable missing data: the lack of an asymptotically chi-square distributed goodness-of-fit statistic. We show that the Supplemented EM algorithm provides a convenient…
An experimentally determined evolutionary model dramatically improves phylogenetic fit.
Bloom, Jesse D
2014-08-01
All modern approaches to molecular phylogenetics require a quantitative model for how genes evolve. Unfortunately, existing evolutionary models do not realistically represent the site-heterogeneous selection that governs actual sequence change. Attempts to remedy this problem have involved augmenting these models with a burgeoning number of free parameters. Here, I demonstrate an alternative: Experimental determination of a parameter-free evolutionary model via mutagenesis, functional selection, and deep sequencing. Using this strategy, I create an evolutionary model for influenza nucleoprotein that describes the gene phylogeny far better than existing models with dozens or even hundreds of free parameters. Emerging high-throughput experimental strategies such as the one employed here provide fundamentally new information that has the potential to transform the sensitivity of phylogenetic and genetic analyses. PMID:24859245
Diploid biological evolution models with general smooth fitness landscapes and recombination.
Saakian, David B; Kirakosyan, Zara; Hu, Chin-Kun
2008-06-01
Using a Hamilton-Jacobi equation approach, we obtain analytic equations for steady-state population distributions and mean fitness functions for Crow-Kimura and Eigen-type diploid biological evolution models with general smooth hypergeometric fitness landscapes. Our numerical solutions of diploid biological evolution models confirm the analytic equations obtained. We also study the parallel diploid model for the simple case of recombination and calculate the variance of distribution, which is consistent with numerical results. PMID:18643300
Individual Differences and Fitting Methods for the Two-Choice Diffusion Model of Decision Making
Ratcliff, Roger; Childers, Russ
2015-01-01
Methods of fitting the diffusion model were examined with a focus on what the model can tell us about individual differences. Diffusion model parameters were obtained from the fits to data from two experiments and consistency of parameter values, individual differences, and practice effects were examined using different numbers of observations from each subject. Two issues were examined, first, what sizes of differences between groups can be obtained to distinguish between groups and second, what sizes of differences would be needed to find individual subjects that had a deficit relative to a control group. The parameter values from the experiments provided ranges that were used in a simulation study to examine recovery of individual differences. This study used several diffusion model fitting programs, fitting methods, and published packages. In a second simulation study, 64 sets of simulated data from each of 48 sets of parameter values (spanning the range of typical values obtained from fits to data) were fit with the different methods and biases and standard deviations in recovered model parameters were compared across methods. Finally, in a third simulation study, a comparison between a standard chi-square method and a hierarchical Bayesian method was performed. The results from these studies can be used as a starting point for selecting fitting methods and as a basis for understanding the strengths and weaknesses of using diffusion model analyses to examine individual differences in clinical, neuropsychological, and educational testing. PMID:26236754
Fitting Partially Nonlinear Random Coefficient Models as SEMs
ERIC Educational Resources Information Center
Harring, Jeffrey R.; Cudeck, Robert; du Toit, Stephen H. C.
2006-01-01
The nonlinear random coefficient model has become increasingly popular as a method for describing individual differences in longitudinal research. Although promising, the nonlinear model it is not utilized as often as it might be because software options are still somewhat limited. In this article we show that a specialized version of the model…
Fitting Computational Models to fMRI Data
Ashby, F. Gregory; Waldschmidt, Jennifer G.
2008-01-01
Many computational models in psychology predict how neural activation in specific brain regions should change during certain cognitive tasks. The emergence of fMRI as a research tool provides an ideal vehicle to test these predictions. Before such tests are possible, however, significant methodological problems must be solved. These problems include transforming the neural activations predicted by the model into predicted BOLD responses, identifying the voxels within each region of interest against which to test the model, and comparing the observed and predicted BOLD responses in each of these regions. Methods are described for solving each of these problems. PMID:18697666
Fitting degradation of shoreline scarps by a nonlinear diffusion model
Andrews, D.J.; Buckna, R.C.
1987-01-01
The diffusion model of degradation of topographic features is a promising means by which vertical offsets on Holocene faults might be dated. In order to calibrate the method, we have examined present-day profiles of wave-cut shoreline scarps of late Pleistocene lakes Bonneville and Lahontan. A table is included that allows easy application of the model to scarps with simple initial shape. -from Authors
NASA Astrophysics Data System (ADS)
Jain, Jalaj; Prakash, Ram; Vyas, Gheesa Lal; Pal, Udit Narayan; Chowdhuri, Malay Bikas; Manchanda, Ranjana; Halder, Nilanjan; Choyal, Yaduvendra
2015-12-01
In the present work an effort has been made to estimate the plasma parameters simultaneously like—electron density, electron temperature, ground state atom density, ground state ion density and metastable state density from the observed visible spectra of penning plasma discharge (PPD) source using least square fitting. The analysis is performed for the prominently observed neutral helium lines. The atomic data and analysis structure (ADAS) database is used to provide the required collisional-radiative (CR) photon emissivity coefficients (PECs) values under the optical thin plasma condition in the analysis. With this condition the estimated plasma temperature from the PPD is found rather high. It is seen that the inclusion of opacity in the observed spectral lines through PECs and addition of diffusion of neutrals and metastable state species in the CR-model code analysis improves the electron temperature estimation in the simultaneous measurement.
Atmospheric Turbulence Modeling for Aero Vehicles: Fractional Order Fits
NASA Technical Reports Server (NTRS)
Kopasakis, George
2015-01-01
Atmospheric turbulence models are necessary for the design of both inlet/engine and flight controls, as well as for studying coupling between the propulsion and the vehicle structural dynamics for supersonic vehicles. Models based on the Kolmogorov spectrum have been previously utilized to model atmospheric turbulence. In this paper, a more accurate model is developed in its representative fractional order form, typical of atmospheric disturbances. This is accomplished by first scaling the Kolmogorov spectral to convert them into finite energy von Karman forms and then by deriving an explicit fractional circuit-filter type analog for this model. This circuit model is utilized to develop a generalized formulation in frequency domain to approximate the fractional order with the products of first order transfer functions, which enables accurate time domain simulations. The objective of this work is as follows. Given the parameters describing the conditions of atmospheric disturbances, and utilizing the derived formulations, directly compute the transfer function poles and zeros describing these disturbances for acoustic velocity, temperature, pressure, and density. Time domain simulations of representative atmospheric turbulence can then be developed by utilizing these computed transfer functions together with the disturbance frequencies of interest.
Atmospheric Turbulence Modeling for Aero Vehicles: Fractional Order Fits
NASA Technical Reports Server (NTRS)
Kopasakis, George
2010-01-01
Atmospheric turbulence models are necessary for the design of both inlet/engine and flight controls, as well as for studying coupling between the propulsion and the vehicle structural dynamics for supersonic vehicles. Models based on the Kolmogorov spectrum have been previously utilized to model atmospheric turbulence. In this paper, a more accurate model is developed in its representative fractional order form, typical of atmospheric disturbances. This is accomplished by first scaling the Kolmogorov spectral to convert them into finite energy von Karman forms and then by deriving an explicit fractional circuit-filter type analog for this model. This circuit model is utilized to develop a generalized formulation in frequency domain to approximate the fractional order with the products of first order transfer functions, which enables accurate time domain simulations. The objective of this work is as follows. Given the parameters describing the conditions of atmospheric disturbances, and utilizing the derived formulations, directly compute the transfer function poles and zeros describing these disturbances for acoustic velocity, temperature, pressure, and density. Time domain simulations of representative atmospheric turbulence can then be developed by utilizing these computed transfer functions together with the disturbance frequencies of interest.
Two Dimensional Non-commutative Space and Rydberg Atom Model
NASA Astrophysics Data System (ADS)
Chung, Won Sang
2015-06-01
In this paper we consider the case of only space-space non-commutativity in two dimension. We also discuss the Rydberg atom model in this space and use the linear realization of the coordinate and momentum operators to solve the Schrödinger equation for the Rydberg atom through the standard perturbation method. Finally, the thermodynamics for the Rydberg atom model is discussed.
Performance of Transit Model Fitting in Processing Four Years of Kepler Science Data
NASA Astrophysics Data System (ADS)
Li, Jie; Burke, Christopher J.; Jenkins, Jon Michael; Quintana, Elisa V.; Rowe, Jason; Seader, Shawn; Tenenbaum, Peter; Twicken, Joseph D.
2014-06-01
We present transit model fitting performance of the Kepler Science Operations Center (SOC) Pipeline in processing four years of science data, which were collected by the Kepler spacecraft from May 13, 2009 to May 12, 2013. Threshold Crossing Events (TCEs), which represent transiting planet detections, are generated by the Transiting Planet Search (TPS) component of the pipeline and subsequently processed in the Data Validation (DV) component. The transit model is used in DV to fit TCEs and derive parameters that are used in various diagnostic tests to validate planetary candidates. The standard transit model includes five fit parameters: transit epoch time (i.e. central time of first transit), orbital period, impact parameter, ratio of planet radius to star radius and ratio of semi-major axis to star radius. In the latest Kepler SOC pipeline codebase, the light curve of the target for which a TCE is generated is initially fitted by a trapezoidal model with four parameters: transit epoch time, depth, duration and ingress time. The trapezoidal model fit, implemented with repeated Levenberg-Marquardt minimization, provides a quick and high fidelity assessment of the transit signal. The fit parameters of the trapezoidal model with the minimum chi-square metric are converted to set initial values of the fit parameters of the standard transit model. Additional parameters, such as the equilibrium temperature and effective stellar flux of the planet candidate, are derived from the fit parameters of the standard transit model to characterize pipeline candidates for the search of Earth-size planets in the Habitable Zone. The uncertainties of all derived parameters are updated in the latest codebase to take into account for the propagated errors of the fit parameters as well as the uncertainties in stellar parameters. The results of the transit model fitting of the TCEs identified by the Kepler SOC Pipeline, including fitted and derived parameters, fit goodness metrics and
A no-scale inflationary model to fit them all
Ellis, John; García, Marcos A.G.; Olive, Keith A.; Nanopoulos, Dimitri V. E-mail: garciagarcia@physics.umn.edu E-mail: olive@physics.umn.edu
2014-08-01
The magnitude of B-mode polarization in the cosmic microwave background as measured by BICEP2 favours models of chaotic inflation with a quadratic m{sup 2} φ{sup 2}/2 potential, whereas data from the Planck satellite favour a small value of the tensor-to-scalar perturbation ratio r that is highly consistent with the Starobinsky R +R{sup 2} model. Reality may lie somewhere between these two scenarios. In this paper we propose a minimal two-field no-scale supergravity model that interpolates between quadratic and Starobinsky-like inflation as limiting cases, while retaining the successful prediction n{sub s} ≅ 0.96.
Design of spatial experiments: Model fitting and prediction
Fedorov, V.V.
1996-03-01
The main objective of the paper is to describe and develop model oriented methods and algorithms for the design of spatial experiments. Unlike many other publications in this area, the approach proposed here is essentially based on the ideas of convex design theory.
Using proper regression methods for fitting the Langmuir model to sorption data
Technology Transfer Automated Retrieval System (TEKTRAN)
The Langmuir model, originally developed for the study of gas sorption to surfaces, is one of the most commonly used models for fitting phosphorus sorption data. There are good theoretical reasons, however, against applying this model to describe P sorption to soils. Nevertheless, the Langmuir model...
Perturbed atoms in molecules and solids: The PATMOS model
NASA Astrophysics Data System (ADS)
Røeggen, Inge; Gao, Bin
2013-09-01
A new computational method for electronic-structure studies of molecules and solids is presented. The key element in the new model - denoted the perturbed atoms in molecules and solids model - is the concept of a perturbed atom in a complex. The basic approximation of the new model is unrestricted Hartree Fock (UHF). The UHF orbitals are localized by the Edmiston-Ruedenberg procedure. The perturbed atoms are defined by distributing the orbitals among the nuclei in such a way that the sum of the intra-atomic UHF energies has a minimum. Energy corrections with respect to the UHF energy, are calculated within the energy incremental scheme. The most important three- and four-electron corrections are selected by introducing a modified geminal approach. Test calculations are performed on N2, Li2, and parallel arrays of hydrogen atoms. The character of the perturbed atoms is illustrated by calculations on H2, CH4, and C6H6.
Perturbed atoms in molecules and solids: The PATMOS model.
Røeggen, Inge; Gao, Bin
2013-09-01
A new computational method for electronic-structure studies of molecules and solids is presented. The key element in the new model - denoted the perturbed atoms in molecules and solids model - is the concept of a perturbed atom in a complex. The basic approximation of the new model is unrestricted Hartree Fock (UHF). The UHF orbitals are localized by the Edmiston-Ruedenberg procedure. The perturbed atoms are defined by distributing the orbitals among the nuclei in such a way that the sum of the intra-atomic UHF energies has a minimum. Energy corrections with respect to the UHF energy, are calculated within the energy incremental scheme. The most important three- and four-electron corrections are selected by introducing a modified geminal approach. Test calculations are performed on N2, Li2, and parallel arrays of hydrogen atoms. The character of the perturbed atoms is illustrated by calculations on H2, CH4, and C6H6. PMID:24028099
ERIC Educational Resources Information Center
Kiers, Henk A. L.
1989-01-01
An alternating least squares algorithm is offered for fitting the DEcomposition into DIrectional COMponents (DEDICOM) model for representing asymmetric relations among a set of objects via a set of coordinates for the objects on a limited number of dimensions. An algorithm is presented for fitting the IDIOSCAL model in the least squares sense.…
Fitting the Balding-Nichols model to forensic databases.
Rohlfs, Rori V; Aguiar, Vitor R C; Lohmueller, Kirk E; Castro, Amanda M; Ferreira, Alessandro C S; Almeida, Vanessa C O; Louro, Iuri D; Nielsen, Rasmus
2015-11-01
Large forensic databases provide an opportunity to compare observed empirical rates of genotype matching with those expected under forensic genetic models. A number of researchers have taken advantage of this opportunity to validate some forensic genetic approaches, particularly to ensure that estimated rates of genotype matching between unrelated individuals are indeed slight overestimates of those observed. However, these studies have also revealed systematic error trends in genotype probability estimates. In this analysis, we investigate these error trends and show how they result from inappropriate implementation of the Balding-Nichols model in the context of database-wide matching. Specifically, we show that in addition to accounting for increased allelic matching between individuals with recent shared ancestry, studies must account for relatively decreased allelic matching between individuals with more ancient shared ancestry. PMID:26186694
Parameter fitting for piano sound synthesis by physical modeling
NASA Astrophysics Data System (ADS)
Bensa, Julien; Gipouloux, Olivier; Kronland-Martinet, Richard
2005-07-01
A difficult issue in the synthesis of piano tones by physical models is to choose the values of the parameters governing the hammer-string model. In fact, these parameters are hard to estimate from static measurements, causing the synthesis sounds to be unrealistic. An original approach that estimates the parameters of a piano model, from the measurement of the string vibration, by minimizing a perceptual criterion is proposed. The minimization process that was used is a combination of a gradient method and a simulated annealing algorithm, in order to avoid convergence problems in case of multiple local minima. The criterion, based on the tristimulus concept, takes into account the spectral energy density in three bands, each allowing particular parameters to be estimated. The optimization process has been run on signals measured on an experimental setup. The parameters thus estimated provided a better sound quality than the one obtained using a global energetic criterion. Both the sound's attack and its brightness were better preserved. This quality gain was obtained for parameter values very close to the initial ones, showing that only slight deviations are necessary to make synthetic sounds closer to the real ones.
A model for programmatic assessment fit for purpose.
van der Vleuten, C P M; Schuwirth, L W T; Driessen, E W; Dijkstra, J; Tigelaar, D; Baartman, L K J; van Tartwijk, J
2012-01-01
We propose a model for programmatic assessment in action, which simultaneously optimises assessment for learning and assessment for decision making about learner progress. This model is based on a set of assessment principles that are interpreted from empirical research. It specifies cycles of training, assessment and learner support activities that are complemented by intermediate and final moments of evaluation on aggregated assessment data points. A key principle is that individual data points are maximised for learning and feedback value, whereas high-stake decisions are based on the aggregation of many data points. Expert judgement plays an important role in the programme. Fundamental is the notion of sampling and bias reduction to deal with the inevitable subjectivity of this type of judgement. Bias reduction is further sought in procedural assessment strategies derived from criteria for qualitative research. We discuss a number of challenges and opportunities around the proposed model. One of its prime virtues is that it enables assessment to move, beyond the dominant psychometric discourse with its focus on individual instruments, towards a systems approach to assessment design underpinned by empirically grounded theory. PMID:22364452
CPOPT : optimization for fitting CANDECOMP/PARAFAC models.
Dunlavy, Daniel M.; Kolda, Tamara Gibson; Acar, Evrim
2008-10-01
Tensor decompositions (e.g., higher-order analogues of matrix decompositions) are powerful tools for data analysis. In particular, the CANDECOMP/PARAFAC (CP) model has proved useful in many applications such chemometrics, signal processing, and web analysis; see for details. The problem of computing the CP decomposition is typically solved using an alternating least squares (ALS) approach. We discuss the use of optimization-based algorithms for CP, including how to efficiently compute the derivatives necessary for the optimization methods. Numerical studies highlight the positive features of our CPOPT algorithms, as compared with ALS and Gauss-Newton approaches.
Modeling epidemics of multidrug-resistant M. tuberculosis of heterogeneous fitness.
Cohen, Ted; Murray, Megan
2004-10-01
Mathematical models have recently been used to predict the future burden of multidrug-resistant tuberculosis (MDRTB). These models suggest the threat of multidrug resistance to TB control will depend on the relative 'fitness' of MDR strains and imply that if the average fitness of MDR strains is considerably less than that of drug-sensitive strains, the emergence of resistance will not jeopardize the success of tuberculosis control efforts. Multidrug resistance in M. tuberculosis is conferred by the sequential acquisition of a number of different single-locus mutations that have been shown to have heterogeneous phenotypic effects. Here we model the impact of initial fitness estimates on the emergence of MDRTB assuming that the relative fitness of MDR strains is heterogeneous. We find that even when the average relative fitness of MDR strains is low and a well-functioning control program is in place, a small subpopulation of a relatively fit MDR strain may eventually outcompete both the drug-sensitive strains and the less fit MDR strains. These results imply that current epidemiological measures and short-term trends in the burden of MDRTB do not provide evidence that MDRTB strains can be contained in the absence of specific efforts to limit transmission from those with MDR disease. PMID:15378056
"Piekara's Chair": Mechanical Model for Atomic Energy Levels.
ERIC Educational Resources Information Center
Golab-Meyer, Zofia
1991-01-01
Uses the teaching method of models or analogies, specifically the model called "Piekara's chair," to show how teaching classical mechanics can familiarize students with the notion of energy levels in atomic physics. (MDH)
Proposed reference models for atomic oxygen in the terrestrial atmosphere
NASA Technical Reports Server (NTRS)
Llewellyn, E. J.; Mcdade, I. C.; Lockerbie, M. D.
1989-01-01
A provisional Atomic Oxygen Reference model was derived from average monthly ozone profiles and the MSIS-86 reference model atmosphere. The concentrations are presented in tabular form for the altitude range 40 to 130 km.
The Quantum Atomic Model "Electronium": A Successful Teaching Tool.
ERIC Educational Resources Information Center
Budde, Marion; Niedderer, Hans; Scott, Philip; Leach, John
2002-01-01
Focuses on the quantum atomic model Electronium. Outlines the Bremen teaching approach in which this model is used, and analyzes the learning of two students as they progress through the teaching unit. (Author/MM)
Developing Models: What is the Atom Really Like?
ERIC Educational Resources Information Center
Records, Roger M.
1982-01-01
Five atomic theory activities feasible for high school students to perform are described based on the following models: (1) Dalton's Uniform Sphere Model; (2) Thomson's Raisin Pudding Model; (3) Rutherford's Nuclear Model; (4) Bohr's Energy Level Model, and (5) Orbital Model from quantum mechanics. (SK)
Are pollination "syndromes" predictive? Asian dalechampia fit neotropical models.
Armbruster, W Scott; Gong, Yan-Bing; Huang, Shuang-Quan
2011-07-01
Using pollination syndrome parameters and pollinator correlations with floral phenotype from the Neotropics, we predicted that Dalechampia bidentata Blume (Euphorbiaceae) in southern China would be pollinated by female resin-collecting bees between 12 and 20 mm in length. Observations in southwestern Yunnan Province, China, revealed pollination primarily by resin-collecting female Megachile (Callomegachile) faceta Bingham (Hymenoptera: Megachilidae). These bees, at 14 mm in length, were in the predicted size range, confirming the utility of syndromes and models developed in distant regions. Phenotypic selection analyses and estimation of adaptive surfaces and adaptive accuracies together suggest that the blossoms of D. bidentata are well adapted to pollination by their most common floral visitors. PMID:21670584
Sader, John E.; Yousefi, Morteza; Friend, James R.
2014-02-15
Thermal noise spectra of nanomechanical resonators are used widely to characterize their physical properties. These spectra typically exhibit a Lorentzian response, with additional white noise due to extraneous processes. Least-squares fits of these measurements enable extraction of key parameters of the resonator, including its resonant frequency, quality factor, and stiffness. Here, we present general formulas for the uncertainties in these fit parameters due to sampling noise inherent in all thermal noise spectra. Good agreement with Monte Carlo simulation of synthetic data and measurements of an Atomic Force Microscope (AFM) cantilever is demonstrated. These formulas enable robust interpretation of thermal noise spectra measurements commonly performed in the AFM and adaptive control of fitting procedures with specified tolerances.
Adaptation in tunably rugged fitness landscapes: the rough Mount Fuji model.
Neidhart, Johannes; Szendro, Ivan G; Krug, Joachim
2014-10-01
Much of the current theory of adaptation is based on Gillespie's mutational landscape model (MLM), which assumes that the fitness values of genotypes linked by single mutational steps are independent random variables. On the other hand, a growing body of empirical evidence shows that real fitness landscapes, while possessing a considerable amount of ruggedness, are smoother than predicted by the MLM. In the present article we propose and analyze a simple fitness landscape model with tunable ruggedness based on the rough Mount Fuji (RMF) model originally introduced by Aita et al. in the context of protein evolution. We provide a comprehensive collection of results pertaining to the topographical structure of RMF landscapes, including explicit formulas for the expected number of local fitness maxima, the location of the global peak, and the fitness correlation function. The statistics of single and multiple adaptive steps on the RMF landscape are explored mainly through simulations, and the results are compared to the known behavior in the MLM model. Finally, we show that the RMF model can explain the large number of second-step mutations observed on a highly fit first-step background in a recent evolution experiment with a microvirid bacteriophage. PMID:25123507
Adaptation in Tunably Rugged Fitness Landscapes: The Rough Mount Fuji Model
Neidhart, Johannes; Szendro, Ivan G.; Krug, Joachim
2014-01-01
Much of the current theory of adaptation is based on Gillespie’s mutational landscape model (MLM), which assumes that the fitness values of genotypes linked by single mutational steps are independent random variables. On the other hand, a growing body of empirical evidence shows that real fitness landscapes, while possessing a considerable amount of ruggedness, are smoother than predicted by the MLM. In the present article we propose and analyze a simple fitness landscape model with tunable ruggedness based on the rough Mount Fuji (RMF) model originally introduced by Aita et al. in the context of protein evolution. We provide a comprehensive collection of results pertaining to the topographical structure of RMF landscapes, including explicit formulas for the expected number of local fitness maxima, the location of the global peak, and the fitness correlation function. The statistics of single and multiple adaptive steps on the RMF landscape are explored mainly through simulations, and the results are compared to the known behavior in the MLM model. Finally, we show that the RMF model can explain the large number of second-step mutations observed on a highly fit first-step background in a recent evolution experiment with a microvirid bacteriophage. PMID:25123507
Martin, Guillaume; Lenormand, Thomas
2015-06-01
When are mutations beneficial in one environment and deleterious in another? More generally, what is the relationship between mutation effects across environments? These questions are crucial to predict adaptation in heterogeneous conditions in a broad sense. Empirical evidence documents various patterns of fitness effects across environments but we still lack a framework to analyze these multivariate data. In this article, we extend Fisher's geometrical model to multiple environments determining distinct peaks. We derive the fitness distribution, in one environment, among mutants with a given fitness in another and the bivariate distribution of random mutants' fitnesses across two or more environments. The geometry of the phenotype-fitness landscape is naturally interpreted in terms of fitness trade-offs between environments. These results may be used to fit/predict empirical distributions or to predict the pattern of adaptation across heterogeneous conditions. As an example, we derive the genomic rate of substitution and of adaptation in a metapopulation divided into two distinct habitats in a high migration regime and show that they depend critically on the geometry of the phenotype-fitness landscape. PMID:25908434
Marsh, Rebeccah E; Riauka, Terence A; McQuarrie, Steve A
2007-01-01
Increasingly, fractals are being incorporated into pharmacokinetic models to describe transport and chemical kinetic processes occurring in confined and heterogeneous spaces. However, fractal compartmental models lead to differential equations with power-law time-dependent kinetic rate coefficients that currently are not accommodated by common commercial software programs. This paper describes a parameter optimization method for fitting individual pharmacokinetic curves based on a simulated annealing (SA) algorithm, which always converged towards the global minimum and was independent of the initial parameter values and parameter bounds. In a comparison using a classical compartmental model, similar fits by the Gauss-Newton and Nelder-Mead simplex algorithms required stringent initial estimates and ranges for the model parameters. The SA algorithm is ideal for fitting a wide variety of pharmacokinetic models to clinical data, especially those for which there is weak prior knowledge of the parameter values, such as the fractal models. PMID:17706176
Early atomic models - from mechanical to quantum (1904-1913)
NASA Astrophysics Data System (ADS)
Baily, C.
2013-01-01
A complete history of early atomic models would fill volumes, but a reasonably coherent tale of the path from mechanical atoms to the quantum can be told by focusing on the relevant work of three great contributors to atomic physics, in the critically important years between 1904 and 1913: J.J. Thomson, Ernest Rutherford and Niels Bohr. We first examine the origins of Thomson's mechanical atomic models, from his ethereal vortex atoms in the early 1880's, to the myriad "corpuscular" atoms he proposed following the discovery of the electron in 1897. Beyond qualitative predictions for the periodicity of the elements, the application of Thomson's atoms to problems in scattering and absorption led to quantitative predictions that were confirmed by experiments with high-velocity electrons traversing thin sheets of metal. Still, the much more massive and energetic α-particles being studied by Rutherford were better suited for exploring the interior of the atom, and careful measurements on the angular dependence of their scattering eventually allowed him to infer the existence of an atomic nucleus. Niels Bohr was particularly troubled by the radiative instability inherent to any mechanical atom, and succeeded in 1913 where others had failed in the prediction of emission spectra, by making two bold hypotheses that were in contradiction to the laws of classical physics, but necessary in order to account for experimental facts.
Revisiting a Statistical Shortcoming When Fitting the Langmuir Model to Sorption Data
Technology Transfer Automated Retrieval System (TEKTRAN)
The Langmuir model is commonly used for describing sorption behavior of reactive solutes to surfaces. Fitting the Langmuir model to sorption data requires either the use of nonlinear regression or, alternatively, linear regression using one of the linearized versions of the model. Statistical limit...
Hydrothermal germination models: comparison of two data-fitting approaches with probit optimization
Technology Transfer Automated Retrieval System (TEKTRAN)
Probit models for estimating hydrothermal germination rate yield model parameters that have been associated with specific physiological processes. The desirability of linking germination response to seed physiology must be weighed against expectations of model fit and the relative accuracy of predi...
Asymptotic Fitness Distribution in the Bak-Sneppen Model of Biological Evolution with Four Species
NASA Astrophysics Data System (ADS)
Schlemm, Eckhard
2012-08-01
We suggest a new method to compute the asymptotic fitness distribution in the Bak-Sneppen model of biological evolution. As applications we derive the full asymptotic distribution in the four-species model, and give an explicit linear recurrence relation for a set of coefficients determining the asymptotic distribution in the five-species model.
Modified Likelihood-Based Item Fit Statistics for the Generalized Graded Unfolding Model
ERIC Educational Resources Information Center
Roberts, James S.
2008-01-01
Orlando and Thissen (2000) developed an item fit statistic for binary item response theory (IRT) models known as S-X[superscript 2]. This article generalizes their statistic to polytomous unfolding models. Four alternative formulations of S-X[superscript 2] are developed for the generalized graded unfolding model (GGUM). The GGUM is a…
NASA Astrophysics Data System (ADS)
Shekhar, Karthik; Ruberman, Claire F.; Ferguson, Andrew L.; Barton, John P.; Kardar, Mehran; Chakraborty, Arup K.
2013-12-01
Mutational escape from vaccine-induced immune responses has thwarted the development of a successful vaccine against AIDS, whose causative agent is HIV, a highly mutable virus. Knowing the virus' fitness as a function of its proteomic sequence can enable rational design of potent vaccines, as this information can focus vaccine-induced immune responses to target mutational vulnerabilities of the virus. Spin models have been proposed as a means to infer intrinsic fitness landscapes of HIV proteins from patient-derived viral protein sequences. These sequences are the product of nonequilibrium viral evolution driven by patient-specific immune responses and are subject to phylogenetic constraints. How can such sequence data allow inference of intrinsic fitness landscapes? We combined computer simulations and variational theory á la Feynman to show that, in most circumstances, spin models inferred from patient-derived viral sequences reflect the correct rank order of the fitness of mutant viral strains. Our findings are relevant for diverse viruses.
EFFICIENT FITTING OF MULTIPLANET KEPLERIAN MODELS TO RADIAL VELOCITY AND ASTROMETRY DATA
Wright, J. T.; Howard, A. W.
2009-05-15
We describe a technique for solving for the orbital elements of multiple planets from radial velocity (RV) and/or astrometric data taken with 1 m s{sup -1} and {mu}as precision, appropriate for efforts to detect Earth-massed planets in their stars' habitable zones, such as NASA's proposed Space Interferometry Mission. We include details of calculating analytic derivatives for use in the Levenberg-Marquardt (LM) algorithm for the problems of fitting RV and astrometric data separately and jointly. We also explicate the general method of separating the linear and nonlinear components of a model fit in the context of an LM fit, show how explicit derivatives can be calculated in such a model, and demonstrate the speed up and convergence improvements of such a scheme in the case of a five-planet fit to published RV data for 55 Cnc.
Transit Model Fitting in Processing Four Years of Kepler Science Data: New Features and Performance
NASA Astrophysics Data System (ADS)
Li, Jie; Burke, Christopher; Jenkins, Jon Michael; Quintana, Elisa; Rowe, Jason; Seader, Shawn; Tenenbaum, Peter; Twicken, Joseph
2015-08-01
We present new transit model fitting features and performance of the latest release (9.3, March 2015) of the Kepler Science Operations Center (SOC) Pipeline, which will be used for the final processing of four years of Kepler science data later this year. Threshold Crossing Events (TCEs), which represent transiting planet detections, are generated by the Transiting Planet Search (TPS) component of the pipeline and subsequently processed in the Data Validation (DV) component. The transit model is used in DV to fit TCEs and derive parameters that are used in various diagnostic tests to validate the planet detections. The standard limb-darkened transit model includes five fit parameters: transit epoch time (i.e. central time of first transit), orbital period, impact parameter, ratio of planet radius to star radius and ratio of semi-major axis to star radius. In the latest Kepler SOC pipeline codebase, the light curve of the target for which a TCE is generated is also fitted by a trapezoidal transit model with four parameters: transit epoch time, depth, duration and ratio of ingress time to duration. The fitted trapezoidal transit model is used in the diagnostic tests when the fit with the standard transit model fails or when the fit is not performed, e.g. for suspected eclipsing binaries. Additional parameters, such as the equilibrium temperature and effective stellar flux (i.e. insolation) of the planet candidate, are derived from the transit model fit parameters to characterize pipeline candidates for the search of Earth-size planets in the habitable zone. The uncertainties of all derived parameters are updated in the latest codebase to account for the propagated errors of the fit parameters as well as the uncertainties in stellar parameters. The results of the transit model fitting for the TCEs identified by the Kepler SOC Pipeline are included in the DV reports and one-page report summaries, which are accessible by the science community at NASA Exoplanet Archive
Packard, Gary C
2013-09-01
The ongoing debate about methods for fitting the two-parameter allometric equation y=ax(b) to bivariate data seemed to be resolved recently when three groups of investigators independently reported that statistical models fitted by the traditional allometric method (i.e., by back-transforming a linear model fitted to log-log transformations) typically are superior to models fitted by standard nonlinear regression. However, the narrow focus for the statistical analyses in these investigations compromised the most important of the ensuing conclusions. All the investigations focused on two-parameter power functions and excluded from consideration other simple functions that might better describe pattern in the data; and all relied on Akaike's Information Criterion instead of graphical validation to identify the better statistical model. My re-analysis of data from one of the studies (BMR vs. body mass in mustelid carnivores) revealed (1) that the best descriptor for pattern in the dataset is a straight line and not a two-parameter power function; (2) that a model with additive, normal, heteroscedastic error is superior to one with multiplicative, lognormal, heteroscedastic error; and (3) that Akaike's Information Criterion is not a generally reliable metric for discriminating between models fitted to different distributions. These findings have apparent implications for interpreting the outcomes of all three of the aforementioned studies. Future investigations of allometric variation should adopt a more holistic approach to analysis and not be wedded to the traditional allometric method. PMID:23688506
Project Physics Tests 5, Models of the Atom.
ERIC Educational Resources Information Center
Harvard Univ., Cambridge, MA. Harvard Project Physics.
Test items relating to Project Physics Unit 5 are presented in this booklet. Included are 70 multiple-choice and 23 problem-and-essay questions. Concepts of atomic model are examined on aspects of relativistic corrections, electron emission, photoelectric effects, Compton effect, quantum theories, electrolysis experiments, atomic number and mass,…
100th anniversary of Bohr's model of the atom.
Schwarz, W H Eugen
2013-11-18
In the fall of 1913 Niels Bohr formulated his atomic models at the age of 27. This Essay traces Bohr's fundamental reasoning regarding atomic structure and spectra, the periodic table of the elements, and chemical bonding. His enduring insights and superseded suppositions are also discussed. PMID:24123759
NASA Astrophysics Data System (ADS)
Farrell, Kathryn; Oden, J. Tinsley
2014-07-01
Coarse-grained models of atomic systems, created by aggregating groups of atoms into molecules to reduce the number of degrees of freedom, have been used for decades in important scientific and technological applications. In recent years, interest in developing a more rigorous theory for coarse graining and in assessing the predictivity of coarse-grained models has arisen. In this work, Bayesian methods for the calibration and validation of coarse-grained models of atomistic systems in thermodynamic equilibrium are developed. For specificity, only configurational models of systems in canonical ensembles are considered. Among major challenges in validating coarse-grained models are (1) the development of validation processes that lead to information essential in establishing confidence in the model's ability predict key quantities of interest and (2), above all, the determination of the coarse-grained model itself; that is, the characterization of the molecular architecture, the choice of interaction potentials and thus parameters, which best fit available data. The all-atom model is treated as the "ground truth," and it provides the basis with respect to which properties of the coarse-grained model are compared. This base all-atom model is characterized by an appropriate statistical mechanics framework in this work by canonical ensembles involving only configurational energies. The all-atom model thus supplies data for Bayesian calibration and validation methods for the molecular model. To address the first challenge, we develop priors based on the maximum entropy principle and likelihood functions based on Gaussian approximations of the uncertainties in the parameter-to-observation error. To address challenge (2), we introduce the notion of model plausibilities as a means for model selection. This methodology provides a powerful approach toward constructing coarse-grained models which are most plausible for given all-atom data. We demonstrate the theory and
Unifying distance-based goodness-of-fit indicators for hydrologic model assessment
NASA Astrophysics Data System (ADS)
Cheng, Qinbo; Reinhardt-Imjela, Christian; Chen, Xi; Schulte, Achim
2014-05-01
The goodness-of-fit indicator, i.e. efficiency criterion, is very important for model calibration. However, recently the knowledge about the goodness-of-fit indicators is all empirical and lacks a theoretical support. Based on the likelihood theory, a unified distance-based goodness-of-fit indicator termed BC-GED model is proposed, which uses the Box-Cox (BC) transformation to remove the heteroscedasticity of model errors and the generalized error distribution (GED) with zero-mean to fit the distribution of model errors after BC. The BC-GED model can unify all recent distance-based goodness-of-fit indicators, and reveals the mean square error (MSE) and the mean absolute error (MAE) that are widely used goodness-of-fit indicators imply statistic assumptions that the model errors follow the Gaussian distribution and the Laplace distribution with zero-mean, respectively. The empirical knowledge about goodness-of-fit indicators can be also easily interpreted by BC-GED model, e.g. the sensitivity to high flow of the goodness-of-fit indicators with large power of model errors results from the low probability of large model error in the assumed distribution of these indicators. In order to assess the effect of the parameters (i.e. the BC transformation parameter λ and the GED kurtosis coefficient β also termed the power of model errors) of BC-GED model on hydrologic model calibration, six cases of BC-GED model were applied in Baocun watershed (East China) with SWAT-WB-VSA model. Comparison of the inferred model parameters and model simulation results among the six indicators demonstrates these indicators can be clearly separated two classes by the GED kurtosis β: β >1 and β ≤ 1. SWAT-WB-VSA calibrated by the class β >1 of distance-based goodness-of-fit indicators captures high flow very well and mimics the baseflow very badly, but it calibrated by the class β ≤ 1 mimics the baseflow very well, because first the larger value of β, the greater emphasis is put on
Soft X-ray spectral fits of Geminga with model neutron star atmospheres
NASA Technical Reports Server (NTRS)
Meyer, R. D.; Pavlov, G. G.; Meszaros, P.
1994-01-01
The spectrum of the soft X-ray pulsar Geminga consists of two components, a softer one which can be interpreted as thermal-like radiation from the surface of the neutron star, and a harder one interpreted as radiation from a polar cap heated by relativistic particles. We have fitted the soft spectrum using a detailed magnetized hydrogen atmosphere model. The fitting parameters are the hydrogen column density, the effective temperature T(sub eff), the gravitational redshift z, and the distance to radius ratio, for different values of the magnetic field B. The best fits for this model are obtained when B less than or approximately 1 x 10(exp 12) G and z lies on the upper boundary of the explored range (z = 0.45). The values of T(sub eff) approximately = (2-3) x 10(exp 5) K are a factor of 2-3 times lower than the value of T(sub eff) obtained for blackbody fits with the same z. The lower T(sub eff) increases the compatibility with some proposed schemes for fast neutrino cooling of neutron stars (NSs) by the direct Urca process or by exotic matter, but conventional cooling cannot be excluded. The hydrogen atmosphere fits also imply a smaller distance to Geminga than that inferred from a blackbody fit. An accurate evaluation of the distance would require a better knowledge of the ROSAT Position Sensitive Proportional Counter (PSPC) response to the low-energy region of the incident spectrum. Our modeling of the soft component with a cooler magnetized atmosphere also implies that the hard-component fit requires a characteristic temperature which is higher (by a factor of approximately 2-3) and a surface area which is smaller (by a factor of 10(exp 3), compared to previous blackbody fits.
Fast numerical algorithms for fitting multiresolution hybrid shape models to brain MRI.
Vemuri, B C; Guo, Y; Lai, S H; Leonard, C M
1997-09-01
In this paper, we present new and fast numerical algorithms for shape recovery from brain MRI using multiresolution hybrid shape models. In this modeling framework, shapes are represented by a core rigid shape characterized by a superquadric function and a superimposed displacement function which is characterized by a membrane spline discretized using the finite-element method. Fitting the model to brain MRI data is cast as an energy minimization problem which is solved numerically. We present three new computational methods for model fitting to data. These methods involve novel mathematical derivations that lead to efficient numerical solutions of the model fitting problem. The first method involves using the nonlinear conjugate gradient technique with a diagonal Hessian preconditioner. The second method involves the nonlinear conjugate gradient in the outer loop for solving global parameters of the model and a preconditioned conjugate gradient scheme for solving the local parameters of the model. The third method involves the nonlinear conjugate gradient in the outer loop for solving the global parameters and a combination of the Schur complement formula and the alternating direction-implicit method for solving the local parameters of the model. We demonstrate the efficiency of our model fitting methods via experiments on several MR brain scans. PMID:9873915
Collisional radiative average atom code based on a relativistic Screened Hydrogenic Model
NASA Astrophysics Data System (ADS)
Benita, A. J.; Mínguez, E.; Mendoza, M. A.; Rubiano, J. G.; Gil, J. M.; Rodríguez, R.; Martel, P.
2015-03-01
A steady-state and time-dependent collisional-radiative ''average-atom'' (AA) model (ATMED CR) is presented for the calculation of atomic and radiative properties of plasmas for a wide range of laboratory and theoretical conditions: coronal, local thermodynamic equilibrium or nonlocal thermodynamic equilibrium, optically thin or thick plasmas and photoionized plasmas. The radiative and collisional rates are a set of analytical approximations that compare well with more sophisticated quantum treatment of atomic rates that yield fast calculations. The atomic model is based on a new Relativistic Screened Hydrogenic Model (NRSHM) with a set of universal screening constants including nlj-splitting that has been obtained by fitting to a large database of ionization potentials and excitation energies compiled from the National Institute of Standards and Technology (NIST) database and the Flexible Atomic Code (FAC). The model NRSHM has been validated by comparing the results with ionization energies, transition energies and wave functions computed using sophisticated self-consistent codes and experimental data. All the calculations presented in this work were performed using ATMED CR code.
Development and design of a late-model fitness test instrument based on LabView
NASA Astrophysics Data System (ADS)
Xie, Ying; Wu, Feiqing
2010-12-01
Undergraduates are pioneers of China's modernization program and undertake the historic mission of rejuvenating our nation in the 21st century, whose physical fitness is vital. A smart fitness test system can well help them understand their fitness and health conditions, thus they can choose more suitable approaches and make practical plans for exercising according to their own situation. following the future trends, a Late-model fitness test Instrument based on LabView has been designed to remedy defects of today's instruments. The system hardware consists of fives types of sensors with their peripheral circuits, an acquisition card of NI USB-6251 and a computer, while the system software, on the basis of LabView, includes modules of user register, data acquisition, data process and display, and data storage. The system, featured by modularization and an open structure, is able to be revised according to actual needs. Tests results have verified the system's stability and reliability.
Mimno, David; Blei, David M; Engelhardt, Barbara E
2015-06-30
Admixture models are a ubiquitous approach to capture latent population structure in genetic samples. Despite the widespread application of admixture models, little thought has been devoted to the quality of the model fit or the accuracy of the estimates of parameters of interest for a particular study. Here we develop methods for validating admixture models based on posterior predictive checks (PPCs), a Bayesian method for assessing the quality of fit of a statistical model to a specific dataset. We develop PPCs for five population-level statistics of interest: within-population genetic variation, background linkage disequilibrium, number of ancestral populations, between-population genetic variation, and the downstream use of admixture parameters to correct for population structure in association studies. Using PPCs, we evaluate the quality of the admixture model fit to four qualitatively different population genetic datasets: the population reference sample (POPRES) European individuals, the HapMap phase 3 individuals, continental Indians, and African American individuals. We found that the same model fitted to different genomic studies resulted in highly study-specific results when evaluated using PPCs, illustrating the utility of PPCs for model-based analyses in large genomic studies. PMID:26071445
Detecting Growth Shape Misspecifications in Latent Growth Models: An Evaluation of Fit Indexes
ERIC Educational Resources Information Center
Leite, Walter L.; Stapleton, Laura M.
2011-01-01
In this study, the authors compared the likelihood ratio test and fit indexes for detection of misspecifications of growth shape in latent growth models through a simulation study and a graphical analysis. They found that the likelihood ratio test, MFI, and root mean square error of approximation performed best for detecting model misspecification…
Mimno, David; Blei, David M.; Engelhardt, Barbara E.
2015-01-01
Admixture models are a ubiquitous approach to capture latent population structure in genetic samples. Despite the widespread application of admixture models, little thought has been devoted to the quality of the model fit or the accuracy of the estimates of parameters of interest for a particular study. Here we develop methods for validating admixture models based on posterior predictive checks (PPCs), a Bayesian method for assessing the quality of fit of a statistical model to a specific dataset. We develop PPCs for five population-level statistics of interest: within-population genetic variation, background linkage disequilibrium, number of ancestral populations, between-population genetic variation, and the downstream use of admixture parameters to correct for population structure in association studies. Using PPCs, we evaluate the quality of the admixture model fit to four qualitatively different population genetic datasets: the population reference sample (POPRES) European individuals, the HapMap phase 3 individuals, continental Indians, and African American individuals. We found that the same model fitted to different genomic studies resulted in highly study-specific results when evaluated using PPCs, illustrating the utility of PPCs for model-based analyses in large genomic studies. PMID:26071445
An Assessment of the Nonparametric Approach for Evaluating the Fit of Item Response Models
ERIC Educational Resources Information Center
Liang, Tie; Wells, Craig S.; Hambleton, Ronald K.
2014-01-01
As item response theory has been more widely applied, investigating the fit of a parametric model becomes an important part of the measurement process. There is a lack of promising solutions to the detection of model misfit in IRT. Douglas and Cohen introduced a general nonparametric approach, RISE (Root Integrated Squared Error), for detecting…
Optimization-Based Model Fitting for Latent Class and Latent Profile Analyses
ERIC Educational Resources Information Center
Huang, Guan-Hua; Wang, Su-Mei; Hsu, Chung-Chu
2011-01-01
Statisticians typically estimate the parameters of latent class and latent profile models using the Expectation-Maximization algorithm. This paper proposes an alternative two-stage approach to model fitting. The first stage uses the modified k-means and hierarchical clustering algorithms to identify the latent classes that best satisfy the…
ERIC Educational Resources Information Center
Gentry, Marcia
2010-01-01
This article presents the author's brief comment on Hisham B. Ghassib's "Where Does Creativity Fit into a Productivist Industrial Model of Knowledge Production?" Ghassib (2010) takes the reader through an interesting history of human innovation and processes and situates his theory within a productivist model. The deliberate attention to…
Shot model parameters for Cygnus X-1 through phase portrait fitting
Lochner, J.C.; Swank, J.H.; Szymkowiak, A.E. )
1991-07-01
Shot models for systems having about 1/f power density spectrum are developed by utilizing a distribution of shot durations. Parameters of the distribution are determined by fitting the power spectrum either with analytic forms for the spectrum of a shot model with a given shot profile, or with the spectrum derived from numerical realizations of trial shot models. The shot fraction is specified by fitting the phase portrait, which is a plot of intensity at a given time versus intensity at a delayed time and in principle is sensitive to different shot profiles. These techniques have been extensively applied to the X-ray variability of Cygnus X-1, using HEAO 1 A-2 and an Exosat ME observation. The power spectra suggest models having characteristic shot durations lasting from milliseconds to a few seconds, while the phase portrait fits give shot fractions of about 50 percent. Best fits to the portraits are obtained if the amplitude of the shot is a power-law function of the duration of the shot. These fits prefer shots having a symmetric exponential rise and decay. Results are interpreted in terms of a distribution of magnetic flares in the accretion disk. 30 refs.
The Predicting Model of E-commerce Site Based on the Ideas of Curve Fitting
NASA Astrophysics Data System (ADS)
Tao, Zhang; Li, Zhang; Dingjun, Chen
On the basis of the idea of the second multiplication curve fitting, the number and scale of Chinese E-commerce site is analyzed. A preventing increase model is introduced in this paper, and the model parameters are solved by the software of Matlab. The validity of the preventing increase model is confirmed though the numerical experiment. The experimental results show that the precision of preventing increase model is ideal.
Curve fitting toxicity test data: Which comes first, the dose response or the model?
Gully, J.; Baird, R.; Bottomley, J.
1995-12-31
The probit model frequently does not fit the concentration-response curve of NPDES toxicity test data and non-parametric models must be used instead. The non-parametric models, trimmed Spearman-Karber, IC{sub p}, and linear interpolation, all require a monotonic concentration-response. Any deviation from a monotonic response is smoothed to obtain the desired concentration-response characteristics. Inaccurate point estimates may result from such procedures and can contribute to imprecision in replicate tests. The following study analyzed reference toxicant and effluent data from giant kelp (Macrocystis pyrifera), purple sea urchin (Strongylocentrotus purpuratus), red abalone (Haliotis rufescens), and fathead minnow (Pimephales promelas) bioassays using commercially available curve fitting software. The purpose was to search for alternative parametric models which would reduce the use of non-parametric models for point estimate analysis of toxicity data. Two non-linear models, power and logistic dose-response, were selected as possible alternatives to the probit model based upon their toxicological plausibility and ability to model most data sets examined. Unlike non-parametric procedures, these and all parametric models can be statistically evaluated for fit and significance. The use of the power or logistic dose response models increased the percentage of parametric model fits for each protocol and toxicant combination examined. The precision of the selected non-linear models was also compared with the EPA recommended point estimation models at several effect.levels. In general, precision of the alternative models was equal to or better than the traditional methods. Finally, use of the alternative models usually produced more plausible point estimates in data sets where the effects of smoothing and non-parametric modeling made the point estimate results suspect.
Optimization of Active Muscle Force-Length Models Using Least Squares Curve Fitting.
Mohammed, Goran Abdulrahman; Hou, Ming
2016-03-01
The objective of this paper is to propose an asymmetric Gaussian function as an alternative to the existing active force-length models, and to optimize this model along with several other existing models by using the least squares curve fitting method. The minimal set of coefficients is identified for each of these models to facilitate the least squares curve fitting. Sarcomere simulated data and one set of rabbits extensor digitorum II experimental data are used to illustrate optimal curve fitting of the selected force-length functions. The results shows that all the curves fit reasonably well with the simulated and experimental data, while the Gordon-Huxley-Julian model and asymmetric Gaussian function are better than other functions in terms of statistical test scores root mean squared error and R-squared. However, the differences in RMSE scores are insignificant (0.3-6%) for simulated data and (0.2-5%) for experimental data. The proposed asymmetric Gaussian model and the method of parametrization of this and the other force-length models mentioned above can be used in the studies on active force-length relationships of skeletal muscles that generate forces to cause movements of human and animal bodies. PMID:26276984
A goodness-of-fit test for occupancy models with correlated within-season revisits
Wright, Wilson; Irvine, Kathryn M.; Rodhouse, Thomas J.
2016-01-01
Occupancy modeling is important for exploring species distribution patterns and for conservation monitoring. Within this framework, explicit attention is given to species detection probabilities estimated from replicate surveys to sample units. A central assumption is that replicate surveys are independent Bernoulli trials, but this assumption becomes untenable when ecologists serially deploy remote cameras and acoustic recording devices over days and weeks to survey rare and elusive animals. Proposed solutions involve modifying the detection-level component of the model (e.g., first-order Markov covariate). Evaluating whether a model sufficiently accounts for correlation is imperative, but clear guidance for practitioners is lacking. Currently, an omnibus goodnessof- fit test using a chi-square discrepancy measure on unique detection histories is available for occupancy models (MacKenzie and Bailey, Journal of Agricultural, Biological, and Environmental Statistics, 9, 2004, 300; hereafter, MacKenzie– Bailey test). We propose a join count summary measure adapted from spatial statistics to directly assess correlation after fitting a model. We motivate our work with a dataset of multinight bat call recordings from a pilot study for the North American Bat Monitoring Program. We found in simulations that our join count test was more reliable than the MacKenzie–Bailey test for detecting inadequacy of a model that assumed independence, particularly when serial correlation was low to moderate. A model that included a Markov-structured detection-level covariate produced unbiased occupancy estimates except in the presence of strong serial correlation and a revisit design consisting only of temporal replicates. When applied to two common bat species, our approach illustrates that sophisticated models do not guarantee adequate fit to real data, underscoring the importance of model assessment. Our join count test provides a widely applicable goodness-of-fit test and
Detailed atomic modeling of Sn plasmas for the EUV source
NASA Astrophysics Data System (ADS)
Sasaki, A.; Sunahara, A.; Nishihawra, K.; Nishikawa, T.; Koike, F.; Tanuma, H.
2008-05-01
An atomic model of Sn plasmas is developed to calculate coefficients of radiative transfer, based on the calculated atomic data using the Hullac code. We find that the emission spectrum and conversion efficiency depend critically on the wavelength and spectral structure of the 4d-4f transition arrays. Satellite lines, which have a significant contribution to the emission, are determined after iterative calculations by changing the number of levels in the atomic model. We also correct transition wavelengths through comparison with experiments. Using the present emissivity and opacity, the radiation hydrodynamics simulation will be carried out toward the optimization of the EUV source.
Soluble Model of Evolution and Extinction Dynamics in a Rugged Fitness Landscape
NASA Astrophysics Data System (ADS)
Sibani, Paolo
1997-08-01
We consider a continuum version of a previously introduced and numerically studied model of macroevolution [P. Sibani, M. R. Schimdt, and P. Alstrøm, Phys. Rev. Lett. 75, 2055 (1995)] in which agents evolve by an optimization process in a rugged fitness landscape and die due to their competitive interactions. We first formulate dynamical equations for the fitness distribution and the survival probability. Secondly, we analytically derive the t-2 law which characterizes the lifetime distribution of biological genera. Thirdly, we discuss other dynamical properties of the model as the rate of extinction and conclude with a brief discussion.
NASA Astrophysics Data System (ADS)
Chaney, Andrea; Espinosa, James; Espinosa, James
2006-10-01
At the turn of the twentieth century, physicists and chemists were developing atomic models. Some of the phenomena that they had to explain were the periodic table, the stability of the atom, and the emission spectra. Niels Bohr is known as making the first modern picture that accounted for these. Unknown to much of the physics community is the work of Walter Ritz. His model explained more emission spectra and predates Bohr's work. We will fit several spectra using Ritz's magnetic model for the atom. The problems of stability and chemical periodicity will be shown to be challenges that this model has difficulty solving, but we will present some potentially useful adaptations to the Ritzian atom that can account for them.
Alpha-cluster model of atomic nuclei
NASA Astrophysics Data System (ADS)
Sosin, Zbigniew; Błocki, Jan; Kallunkathariyil, Jinesh; Łukasik, Jerzy; Pawłowski, Piotr
2016-05-01
The description of a nuclear system in its ground state and at low excitations based on the equation of state (EoS) around normal density is presented. In the expansion of the EoS around the saturation point, additional spin polarization terms are taken into account. These terms, together with the standard symmetry term, are responsible for the appearance of the α-like clusters in the ground-state configurations of the N = Z even-even nuclei. At the nuclear surface these clusters can be identified as alpha particles. A correction for the surface effects is introduced for atomic nuclei. Taking into account an additional interaction between clusters the binding energies and sizes of the considered nuclei are very accurately described. The limits of the EoS parameters are established from the properties of the α, 3He and t particles.
MEAMfit: A reference-free modified embedded atom method (RF-MEAM) energy and force-fitting code
NASA Astrophysics Data System (ADS)
Duff, Andrew Ian
2016-06-01
MEAMfit v1.02. Changes: various bug fixes; speed of single-shot energy and force calculations (not optimization) increased by × 10; elements up to Cn (Z = 112) now correctly read from vasprun.xml files; EAM fits now produce Camelion output files; changed max number of vasprun.xml files to 10,000 (an unnecessary lower limit of 10 was allowed in the previous version).
The FIT 2.0 Model - Fuel-cycle Integration and Tradeoffs
Steven J. Piet; Nick R. Soelberg; Layne F. Pincock; Eric L. Shaber; Gregory M Teske
2011-06-01
All mass streams from fuel separation and fabrication are products that must meet some set of product criteria – fuel feedstock impurity limits, waste acceptance criteria (WAC), material storage (if any), or recycle material purity requirements such as zirconium for cladding or lanthanides for industrial use. These must be considered in a systematic and comprehensive way. The FIT model and the “system losses study” team that developed it [Shropshire2009, Piet2010b] are steps by the Fuel Cycle Technology program toward an analysis that accounts for the requirements and capabilities of each fuel cycle component, as well as major material flows within an integrated fuel cycle. This will help the program identify near-term R&D needs and set longer-term goals. This report describes FIT 2, an update of the original FIT model.[Piet2010c] FIT is a method to analyze different fuel cycles; in particular, to determine how changes in one part of a fuel cycle (say, fuel burnup, cooling, or separation efficiencies) chemically affect other parts of the fuel cycle. FIT provides the following: Rough estimate of physics and mass balance feasibility of combinations of technologies. If feasibility is an issue, it provides an estimate of how performance would have to change to achieve feasibility. Estimate of impurities in fuel and impurities in waste as function of separation performance, fuel fabrication, reactor, uranium source, etc.
Fitting the linear quadratic model to detailed data sets for different dose ranges
NASA Astrophysics Data System (ADS)
Garcia, L. M.; Leblanc, J.; Wilkins, D.; Raaphorst, G. P.
2006-06-01
Survival curve behaviour and degree of correspondence between the linear-quadratic (LQ) model and experimental data in an extensive dose range for high dose rates were analysed. Detailed clonogenic assays with irradiation given in 0.5 Gy increments and a total dose range varying from 10.5 to 16 Gy were performed. The cell lines investigated were: CHOAA8 (Chinese hamster fibroblast cells), U373MG (human glioblastoma cells), CP3 and DU145 (human prostate carcinoma cell lines). The analyses were based on χ2-statistics and Monte Carlo simulation of the experiments. A decline of LQ fit quality at very low doses (<2 Gy) is observed. This result can be explained by the hypersensitive effect observed in CHOAA8, U373MG and DU145 data and an adaptive-type response in the CP3 cell line. A clear improvement of the fit is discerned by removing the low dose data points. The fit worsening at high doses also shows that LQ cannot explain this region. This shows that the LQ model fits better the middle dose region of the survival curve. The analysis conducted in our study reveals a dose dependency of the LQ fit in different cell lines.
Burnham, A K
2006-05-17
Chemical kinetic modeling has been used for many years in process optimization, estimating real-time material performance, and lifetime prediction. Chemists have tended towards developing detailed mechanistic models, while engineers have tended towards global or lumped models. Many, if not most, applications use global models by necessity, since it is impractical or impossible to develop a rigorous mechanistic model. Model fitting acquired a bad name in the thermal analysis community after that community realized a decade after other disciplines that deriving kinetic parameters for an assumed model from a single heating rate produced unreliable and sometimes nonsensical results. In its place, advanced isoconversional methods (1), which have their roots in the Friedman (2) and Ozawa-Flynn-Wall (3) methods of the 1960s, have become increasingly popular. In fact, as pointed out by the ICTAC kinetics project in 2000 (4), valid kinetic parameters can be derived by both isoconversional and model fitting methods as long as a diverse set of thermal histories are used to derive the kinetic parameters. The current paper extends the understanding from that project to give a better appreciation of the strengths and weaknesses of isoconversional and model-fitting approaches. Examples are given from a variety of sources, including the former and current ICTAC round-robin exercises, data sets for materials of interest, and simulated data sets.
Clavijo-Baque, Sabrina; Bozinovic, Francisco
2012-01-01
The origin of endothermy is a puzzling phenomenon in the evolution of vertebrates. To address this issue several explicative models have been proposed. The main models proposed for the origin of endothermy are the aerobic capacity, the thermoregulatory and the parental care models. Our main proposal is that to compare the alternative models, a critical aspect is to determine how strongly natural selection was influenced by body temperature, and basal and maximum metabolic rates during the evolution of endothermy. We evaluate these relationships in the context of three main hypotheses aimed at explaining the evolution of endothermy, namely the parental care hypothesis and two hypotheses related to the thermoregulatory model (thermogenic capacity and higher body temperature models). We used data on basal and maximum metabolic rates and body temperature from 17 rodent populations, and used intrinsic population growth rate (Rmax) as a global proxy of fitness. We found greater support for the thermogenic capacity model of the thermoregulatory model. In other words, greater thermogenic capacity is associated with increased fitness in rodent populations. To our knowledge, this is the first test of the fitness consequences of the thermoregulatory and parental care models for the origin of endothermy. PMID:22606328
Velasco, Jose; Pizarro, Daniel; Macias-Guarasa, Javier
2012-01-01
This paper presents a novel approach for indoor acoustic source localization using sensor arrays. The proposed solution starts by defining a generative model, designed to explain the acoustic power maps obtained by Steered Response Power (SRP) strategies. An optimization approach is then proposed to fit the model to real input SRP data and estimate the position of the acoustic source. Adequately fitting the model to real SRP data, where noise and other unmodelled effects distort the ideal signal, is the core contribution of the paper. Two basic strategies in the optimization are proposed. First, sparse constraints in the parameters of the model are included, enforcing the number of simultaneous active sources to be limited. Second, subspace analysis is used to filter out portions of the input signal that cannot be explained by the model. Experimental results on a realistic speech database show statistically significant localization error reductions of up to 30% when compared with the SRP-PHAT strategies. PMID:23202021
Aeroelastic modeling for the FIT team F/A-18 simulation
NASA Technical Reports Server (NTRS)
Zeiler, Thomas A.; Wieseman, Carol D.
1989-01-01
Some details of the aeroelastic modeling of the F/A-18 aircraft done for the Functional Integration Technology (FIT) team's research in integrated dynamics modeling and how these are combined with the FIT team's integrated dynamics model are described. Also described are mean axis corrections to elastic modes, the addition of nonlinear inertial coupling terms into the equations of motion, and the calculation of internal loads time histories using the integrated dynamics model in a batch simulation program. A video tape made of a loads time history animation was included as a part of the oral presentation. Also discussed is work done in one of the areas of unsteady aerodynamic modeling identified as needing improvement, specifically, in correction factor methodologies for improving the accuracy of stability derivatives calculated with a doublet lattice code.
Model fitting of the kinematics of ten superluminal components in blazar 3C 279
NASA Astrophysics Data System (ADS)
Qian, Shan-Jie
2013-07-01
The kinematics of ten superluminal components (C11- C16, C18, C20, C21 and C24) of blazar 3C 279 are studied from VLBI observations. It is shown that their initial trajectory, distance from the core and apparent speed can be well fitted by the precession model proposed by Qian. Combined with the results of the model fit for the six superluminal components (C3, C4, C7a, C8, C9 and C10) already published, the kinematics of sixteen superluminal components can now be consistently interpreted in the precession scenario with their ejection times spanning more than 25 yr (or more than one precession period). The results from model fitting show the possible existence of a common precessing trajectory for these knots within a projected core distance of ~0.2-0.4 mas. In the framework of the jet-precession scenario, we can, for the first time, identify three classes of trajectories which are characterized by their collimation parameters. These different trajectories could be related to the helical structure of magnetic fields in the jet. Through fitting the model, the bulk Lorentz factor, Doppler factor and viewing angle of these knots are derived. It is found that there is no evidence for any correlation between the bulk Lorentz factor of the components and their precession phase (or ejection time). In a companion paper, the kinematics of another seven components (C5a, C6, C7, C17, C19, C22 and C23) have been derived from model fitting, and a binary black-hole/jet scenario was envisaged. The precession model proposed by Qian would be useful for understanding the kinematics of superluminal components in blazar 3C 279 derived from VLBI observations, by disentangling different mechanisms and ingredients. More generally, it might also be helpful for studying the mechanism of jet swing (wobbling) in other blazars.
ERIC Educational Resources Information Center
Neber, Heinz
2010-01-01
In this article, the author presents his comments on Hisham Ghassib's article entitled "Where Does Creativity Fit into the Productivist Industrial Model of Knowledge Production?" Ghassib (2010) describes historical transformations of science from a marginal and non-autonomous activity which had been constrained by traditions to a self-autonomous,…
Examining Creative Performance in the Workplace through a Person-Environment Fit Model.
ERIC Educational Resources Information Center
Puccio, Gerard J.; Talbot, Reginald J.; Joniak, Andrew J.
2000-01-01
A modified version of Kirton's Adaptor-Innovator Inventory was used to operationalize the person-environment fit model and a self-report measure was used to assess creative productivity in 40 British adults. Results indicate that style match between the individual and the environment was associated with higher levels of product novelty and…
On Fitting Nonlinear Latent Curve Models to Multiple Variables Measured Longitudinally
ERIC Educational Resources Information Center
Blozis, Shelley A.
2007-01-01
This article shows how nonlinear latent curve models may be fitted for simultaneous analysis of multiple variables measured longitudinally using Mx statistical software. Longitudinal studies often involve observation of several variables across time with interest in the associations between change characteristics of different variables measured…
ERIC Educational Resources Information Center
Wang, Chee Keng John; Pyun, Do Young; Liu, Woon Chia; Lim, Boon San Coral; Li, Fuzhong
2013-01-01
Using a multilevel latent growth curve modeling (LGCM) approach, this study examined longitudinal change in levels of physical fitness performance over time (i.e. four years) in young adolescents aged from 12-13 years. The sample consisted of 6622 students from 138 secondary schools in Singapore. Initial analyses found between-school variation on…
Super Kids--Superfit. A Comprehensive Fitness Intervention Model for Elementary Schools.
ERIC Educational Resources Information Center
Virgilio, Stephen J.; Berenson, Gerald S.
1988-01-01
Objectives and activities of the cardiovascular (CV) fitness program Super Kids--Superfit are related in this article. This exercise program is one component of the Heart Smart Program, a CV health intervention model for elementary school students. Program evaluation, parent education, and school and community intervention strategies are…
Haberman, Shelby J; Sinharay, Sandip; Chon, Kyong Hee
2013-07-01
Residual analysis (e.g. Hambleton & Swaminathan, Item response theory: principles and applications, Kluwer Academic, Boston, 1985; Hambleton, Swaminathan, & Rogers, Fundamentals of item response theory, Sage, Newbury Park, 1991) is a popular method to assess fit of item response theory (IRT) models. We suggest a form of residual analysis that may be applied to assess item fit for unidimensional IRT models. The residual analysis consists of a comparison of the maximum-likelihood estimate of the item characteristic curve with an alternative ratio estimate of the item characteristic curve. The large sample distribution of the residual is proved to be standardized normal when the IRT model fits the data. We compare the performance of our suggested residual to the standardized residual of Hambleton et al. (Fundamentals of item response theory, Sage, Newbury Park, 1991) in a detailed simulation study. We then calculate our suggested residuals using data from an operational test. The residuals appear to be useful in assessing the item fit for unidimensional IRT models. PMID:25106393
Impact of Missing Data on Person-Model Fit and Person Trait Estimation
ERIC Educational Resources Information Center
Zhang, Bo; Walker, Cindy M.
2008-01-01
The purpose of this research was to examine the effects of missing data on person-model fit and person trait estimation in tests with dichotomous items. Under the missing-completely-at-random framework, four missing data treatment techniques were investigated including pairwise deletion, coding missing responses as incorrect, hotdeck imputation,…
ERIC Educational Resources Information Center
Harris, Carole Ruth
2010-01-01
This article presents the author's comments on Hisham Ghassib's article entitled "Where Does Creativity Fit into a Productivist Industrial Model of Knowledge Production?" In his article, Ghassib (2010) provides an overview of the philosophical foundations that led to exact science, its role in what was later to become a driving force in the modern…
A Bayesian Approach to Person Fit Analysis in Item Response Theory Models. Research Report.
ERIC Educational Resources Information Center
Glas, Cees A. W.; Meijer, Rob R.
A Bayesian approach to the evaluation of person fit in item response theory (IRT) models is presented. In a posterior predictive check, the observed value on a discrepancy variable is positioned in its posterior distribution. In a Bayesian framework, a Markov Chain Monte Carlo procedure can be used to generate samples of the posterior distribution…