Risk estimation using probability machines
2014-01-01
Background Logistic regression has been the de facto, and often the only, model used in the description and analysis of relationships between a binary outcome and observed features. It is widely used to obtain the conditional probabilities of the outcome given predictors, as well as predictor effect size estimates using conditional odds ratios. Results We show how statistical learning machines for binary outcomes, provably consistent for the nonparametric regression problem, can be used to provide both consistent conditional probability estimation and conditional effect size estimates. Effect size estimates from learning machines leverage our understanding of counterfactual arguments central to the interpretation of such estimates. We show that, if the data generating model is logistic, we can recover accurate probability predictions and effect size estimates with nearly the same efficiency as a correct logistic model, both for main effects and interactions. We also propose a method using learning machines to scan for possible interaction effects quickly and efficiently. Simulations using random forest probability machines are presented. Conclusions The models we propose make no assumptions about the data structure, and capture the patterns in the data by just specifying the predictors involved and not any particular model structure. So they do not run the same risks of model mis-specification and the resultant estimation biases as a logistic model. This methodology, which we call a “risk machine”, will share properties from the statistical machine that it is derived from. PMID:24581306
The quantitative estimation of IT-related risk probabilities.
Herrmann, Andrea
2013-08-01
How well can people estimate IT-related risk? Although estimating risk is a fundamental activity in software management and risk is the basis for many decisions, little is known about how well IT-related risk can be estimated at all. Therefore, we executed a risk estimation experiment with 36 participants. They estimated the probabilities of IT-related risks and we investigated the effect of the following factors on the quality of the risk estimation: the estimator's age, work experience in computing, (self-reported) safety awareness and previous experience with this risk, the absolute value of the risk's probability, and the effect of knowing the estimates of the other participants (see: Delphi method). Our main findings are: risk probabilities are difficult to estimate. Younger and inexperienced estimators were not significantly worse than older and more experienced estimators, but the older and more experienced subjects better used the knowledge gained by knowing the other estimators' results. Persons with higher safety awareness tend to overestimate risk probabilities, but can better estimate ordinal ranks of risk probabilities. Previous own experience with a risk leads to an overestimation of its probability (unlike in other fields like medicine or disasters, where experience with a disease leads to more realistic probability estimates and nonexperience to an underestimation).
Carr, D.B.; Tolley, H.D.
1982-12-01
This paper investigates procedures for univariate nonparametric estimation of tail probabilities. Extrapolated values for tail probabilities beyond the data are also obtained based on the shape of the density in the tail. Several estimators which use exponential weighting are described. These are compared in a Monte Carlo study to nonweighted estimators, to the empirical cdf, to an integrated kernel, to a Fourier series estimate, to a penalized likelihood estimate and a maximum likelihood estimate. Selected weighted estimators are shown to compare favorably to many of these standard estimators for the sampling distributions investigated.
Fall risk probability estimation based on supervised feature learning using public fall datasets.
Koshmak, Gregory A; Linden, Maria; Loutfi, Amy
2016-08-01
Risk of falling is considered among major threats for elderly population and therefore started to play an important role in modern healthcare. With recent development of sensor technology, the number of studies dedicated to reliable fall detection system has increased drastically. However, there is still a lack of universal approach regarding the evaluation of developed algorithms. In the following study we make an attempt to find publicly available fall datasets and analyze similarities among them using supervised learning. After preforming similarity assessment based on multidimensional scaling we indicate the most representative feature vector corresponding to each specific dataset. This vector obtained from a real-life data is subsequently deployed to estimate fall risk probabilities for a statistical fall detection model. Finally, we conclude with some observations regarding the similarity assessment results and provide suggestions towards an efficient approach for evaluation of fall detection studies.
Estimation of the Probability of Labor Force Participation of the AFDC Population-At-Risk
1977-01-01
probability of labor force participation (LFP) of female family heads with dependent children present, the Aid to Families with Dependent Children (AFDC... female and if dependent children were present, which may be viewed as the AFDC pop- ulation-at-risk.l Only those family heads who were in the civilian
Faith, Daniel P
2008-12-01
New species conservation strategies, including the EDGE of Existence (EDGE) program, have expanded threatened species assessments by integrating information about species' phylogenetic distinctiveness. Distinctiveness has been measured through simple scores that assign shared credit among species for evolutionary heritage represented by the deeper phylogenetic branches. A species with a high score combined with a high extinction probability receives high priority for conservation efforts. Simple hypothetical scenarios for phylogenetic trees and extinction probabilities demonstrate how such scoring approaches can provide inefficient priorities for conservation. An existing probabilistic framework derived from the phylogenetic diversity measure (PD) properly captures the idea of shared responsibility for the persistence of evolutionary history. It avoids static scores, takes into account the status of close relatives through their extinction probabilities, and allows for the necessary updating of priorities in light of changes in species threat status. A hypothetical phylogenetic tree illustrates how changes in extinction probabilities of one or more species translate into changes in expected PD. The probabilistic PD framework provided a range of strategies that moved beyond expected PD to better consider worst-case PD losses. In another example, risk aversion gave higher priority to a conservation program that provided a smaller, but less risky, gain in expected PD. The EDGE program could continue to promote a list of top species conservation priorities through application of probabilistic PD and simple estimates of current extinction probability. The list might be a dynamic one, with all the priority scores updated as extinction probabilities change. Results of recent studies suggest that estimation of extinction probabilities derived from the red list criteria linked to changes in species range sizes may provide estimated probabilities for many different species
Probability Surveys, Conditional Probability, and Ecological Risk Assessment
We show that probability-based environmental resource monitoring programs, such as the U.S. Environmental Protection Agency’s (U.S. EPA) Environmental Monitoring and Assessment Program, and conditional probability analysis can serve as a basis for estimating ecological risk over ...
PROBABILITY SURVEYS , CONDITIONAL PROBABILITIES AND ECOLOGICAL RISK ASSESSMENT
We show that probability-based environmental resource monitoring programs, such as the U.S. Environmental Protection Agency's (U.S. EPA) Environmental Monitoring and Assessment Program, and conditional probability analysis can serve as a basis for estimating ecological risk over ...
Point estimates for probability moments
Rosenblueth, Emilio
1975-01-01
Given a well-behaved real function Y of a real random variable X and the first two or three moments of X, expressions are derived for the moments of Y as linear combinations of powers of the point estimates y(x+) and y(x-), where x+ and x- are specific values of X. Higher-order approximations and approximations for discontinuous Y using more point estimates are also given. Second-moment approximations are generalized to the case when Y is a function of several variables. PMID:16578731
Class probability estimation for medical studies.
Simon, Richard
2014-07-01
I provide a commentary on two papers "Probability estimation with machine learning methods for dichotomous and multicategory outcome: Theory" by Jochen Kruppa, Yufeng Liu, Gérard Biau, Michael Kohler, Inke R. König, James D. Malley, and Andreas Ziegler; and "Probability estimation with machine learning methods for dichotomous and multicategory outcome: Applications" by Jochen Kruppa, Yufeng Liu, Hans-Christian Diener, Theresa Holste, Christian Weimar, Inke R. König, and Andreas Ziegler. Those papers provide an up-to-date review of some popular machine learning methods for class probability estimation and compare those methods to logistic regression modeling in real and simulated datasets.
Optimizing Probability of Detection Point Estimate Demonstration
NASA Technical Reports Server (NTRS)
Koshti, Ajay M.
2017-01-01
Probability of detection (POD) analysis is used in assessing reliably detectable flaw size in nondestructive evaluation (NDE). MIL-HDBK-18231and associated mh18232POD software gives most common methods of POD analysis. Real flaws such as cracks and crack-like flaws are desired to be detected using these NDE methods. A reliably detectable crack size is required for safe life analysis of fracture critical parts. The paper provides discussion on optimizing probability of detection (POD) demonstration experiments using Point Estimate Method. POD Point estimate method is used by NASA for qualifying special NDE procedures. The point estimate method uses binomial distribution for probability density. Normally, a set of 29 flaws of same size within some tolerance are used in the demonstration. The optimization is performed to provide acceptable value for probability of passing demonstration (PPD) and achieving acceptable value for probability of false (POF) calls while keeping the flaw sizes in the set as small as possible.
Estimating flood exceedance probabilities in estuarine regions
NASA Astrophysics Data System (ADS)
Westra, Seth; Leonard, Michael
2016-04-01
Flood events in estuarine regions can arise from the interaction of extreme rainfall and storm surge. Determining flood level exceedance probabilities in these regions is complicated by the dependence of these processes for extreme events. A comprehensive study of tide and rainfall gauges along the Australian coastline was conducted to determine the dependence of these extremes using a bivariate logistic threshold-excess model. The dependence strength is shown to vary as a function of distance over many hundreds of kilometres indicating that the dependence arises due to synoptic scale meteorological forcings. It is also shown to vary as a function of storm burst duration, time lag between the extreme rainfall and the storm surge event. The dependence estimates are then used with a bivariate design variable method to determine flood risk in estuarine regions for a number of case studies. Aspects of the method demonstrated in the case studies include, the resolution and range of the hydraulic response table, fitting of probability distributions, computational efficiency, uncertainty, potential variation in marginal distributions due to climate change, and application to two dimensional output from hydraulic models. Case studies are located on the Swan River (Western Australia), Nambucca River and Hawkesbury Nepean River (New South Wales).
Estimating the exceedance probability of extreme rainfalls up to the probable maximum precipitation
NASA Astrophysics Data System (ADS)
Nathan, Rory; Jordan, Phillip; Scorah, Matthew; Lang, Simon; Kuczera, George; Schaefer, Melvin; Weinmann, Erwin
2016-12-01
If risk-based criteria are used in the design of high hazard structures (such as dam spillways and nuclear power stations), then it is necessary to estimate the annual exceedance probability (AEP) of extreme rainfalls up to and including the Probable Maximum Precipitation (PMP). This paper describes the development and application of two largely independent methods to estimate the frequencies of such extreme rainfalls. One method is based on stochastic storm transposition (SST), which combines the "arrival" and "transposition" probabilities of an extreme storm using the total probability theorem. The second method, based on "stochastic storm regression" (SSR), combines frequency curves of point rainfalls with regression estimates of local and transposed areal rainfalls; rainfall maxima are generated by stochastically sampling the independent variates, where the required exceedance probabilities are obtained using the total probability theorem. The methods are applied to two large catchments (with areas of 3550 km2 and 15,280 km2) located in inland southern Australia. Both methods were found to provide similar estimates of the frequency of extreme areal rainfalls for the two study catchments. The best estimates of the AEP of the PMP for the smaller and larger of the catchments were found to be 10-7 and 10-6, respectively, but the uncertainty of these estimates spans one to two orders of magnitude. Additionally, the SST method was applied to a range of locations within a meteorologically homogenous region to investigate the nature of the relationship between the AEP of PMP and catchment area.
Conflict Probability Estimation for Free Flight
NASA Technical Reports Server (NTRS)
Paielli, Russell A.; Erzberger, Heinz
1996-01-01
The safety and efficiency of free flight will benefit from automated conflict prediction and resolution advisories. Conflict prediction is based on trajectory prediction and is less certain the farther in advance the prediction, however. An estimate is therefore needed of the probability that a conflict will occur, given a pair of predicted trajectories and their levels of uncertainty. A method is developed in this paper to estimate that conflict probability. The trajectory prediction errors are modeled as normally distributed, and the two error covariances for an aircraft pair are combined into a single equivalent covariance of the relative position. A coordinate transformation is then used to derive an analytical solution. Numerical examples and Monte Carlo validation are presented.
Actual and actuarial probabilities of competing risks: apples and lemons.
Grunkemeier, Gary L; Jin, Ruyun; Eijkemans, Marinus J C; Takkenberg, Johanna J M
2007-05-01
The probability of a type of failure that is not inevitable, but can be precluded by other events such as death, is given by the cumulative incidence function. In cardiac research articles, it has become known as the actual probability, in contrast to the actuarial methods of estimation, usually implemented by the Kaplan-Meier (KM) estimate. Unlike cumulative incidence, KM attempts to predict what the latent failure probability would be if death were eliminated. To do this, the KM method assumes that the risk of dying and the risk of failure are independent. But this assumption is not true for many cardiac applications in which the risks of failure and death are negatively correlated (ie, patients with a higher risk of dying have a lower risk of failure, and patients with a lower risk of death have a higher risk of failure, which is a condition called informative censoring). Recent editorials in two cardiac journals have promoted the use of the KM method (actuarial estimate) for competing risk events (specifically for heart valve performance) and criticized the use of the cumulative incidence (actual) estimates. This report has two aims: to explain the difference between these two estimates and to show why the KM is generally not appropriate. In the process we will rely on alternative representations of the KM estimator (using redistribution to the right and inverse probability weighting) to explain the difference between the two estimates and to show how it may be possible to adjust KM to overcome the informative censoring.
Estimating the probability of rare events: addressing zero failure data.
Quigley, John; Revie, Matthew
2011-07-01
Traditional statistical procedures for estimating the probability of an event result in an estimate of zero when no events are realized. Alternative inferential procedures have been proposed for the situation where zero events have been realized but often these are ad hoc, relying on selecting methods dependent on the data that have been realized. Such data-dependent inference decisions violate fundamental statistical principles, resulting in estimation procedures whose benefits are difficult to assess. In this article, we propose estimating the probability of an event occurring through minimax inference on the probability that future samples of equal size realize no more events than that in the data on which the inference is based. Although motivated by inference on rare events, the method is not restricted to zero event data and closely approximates the maximum likelihood estimate (MLE) for nonzero data. The use of the minimax procedure provides a risk adverse inferential procedure where there are no events realized. A comparison is made with the MLE and regions of the underlying probability are identified where this approach is superior. Moreover, a comparison is made with three standard approaches to supporting inference where no event data are realized, which we argue are unduly pessimistic. We show that for situations of zero events the estimator can be simply approximated with 1/2.5n, where n is the number of trials.
Estimating Prior Model Probabilities Using an Entropy Principle
NASA Astrophysics Data System (ADS)
Ye, M.; Meyer, P. D.; Neuman, S. P.; Pohlmann, K.
2004-12-01
Considering conceptual model uncertainty is an important process in environmental uncertainty/risk analyses. Bayesian Model Averaging (BMA) (Hoeting et al., 1999) and its Maximum Likelihood version, MLBMA, (Neuman, 2003) jointly assess predictive uncertainty of competing alternative models to avoid bias and underestimation of uncertainty caused by relying on one single model. These methods provide posterior distribution (or, equivalently, leading moments) of quantities of interests for decision-making. One important step of these methods is to specify prior probabilities of alternative models for the calculation of posterior model probabilities. This problem, however, has not been satisfactorily resolved and equally likely prior model probabilities are usually accepted as a neutral choice. Ye et al. (2004) have shown that whereas using equally likely prior model probabilities has led to acceptable geostatistical estimates of log air permeability data from fractured unsaturated tuff at the Apache Leap Research Site (ALRS) in Arizona, identifying more accurate prior probabilities can improve these estimates. In this paper we present a new methodology to evaluate prior model probabilities by maximizing Shannon's entropy with restrictions postulated a priori based on model plausibility relationships. It yields optimum prior model probabilities conditional on prior information used to postulate the restrictions. The restrictions and corresponding prior probabilities can be modified as more information becomes available. The proposed method is relatively easy to use in practice as it is generally less difficult for experts to postulate relationships between models than to specify numerical prior model probability values. Log score, mean square prediction error (MSPE) and mean absolute predictive error (MAPE) criteria consistently show that applying our new method to the ALRS data reduces geostatistical estimation errors provided relationships between models are
PROBABILITY SURVEYS, CONDITIONAL PROBABILITIES, AND ECOLOGICAL RISK ASSESSMENT
We show that probability-based environmental resource monitoring programs, such as U.S. Environmental Protection Agency's (U.S. EPA) Environmental Monitoring and Asscssment Program EMAP) can be analyzed with a conditional probability analysis (CPA) to conduct quantitative probabi...
VOLCANIC RISK ASSESSMENT - PROBABILITY AND CONSEQUENCES
G.A. Valentine; F.V. Perry; S. Dartevelle
2005-08-26
Risk is the product of the probability and consequences of an event. Both of these must be based upon sound science that integrates field data, experiments, and modeling, but must also be useful to decision makers who likely do not understand all aspects of the underlying science. We review a decision framework used in many fields such as performance assessment for hazardous and/or radioactive waste disposal sites that can serve to guide the volcanological community towards integrated risk assessment. In this framework the underlying scientific understanding of processes that affect probability and consequences drive the decision-level results, but in turn these results can drive focused research in areas that cause the greatest level of uncertainty at the decision level. We review two examples of the determination of volcanic event probability: (1) probability of a new volcano forming at the proposed Yucca Mountain radioactive waste repository, and (2) probability that a subsurface repository in Japan would be affected by the nearby formation of a new stratovolcano. We also provide examples of work on consequences of explosive eruptions, within the framework mentioned above. These include field-based studies aimed at providing data for ''closure'' of wall rock erosion terms in a conduit flow model, predictions of dynamic pressure and other variables related to damage by pyroclastic flow into underground structures, and vulnerability criteria for structures subjected to conditions of explosive eruption. Process models (e.g., multiphase flow) are important for testing the validity or relative importance of possible scenarios in a volcanic risk assessment. We show how time-dependent multiphase modeling of explosive ''eruption'' of basaltic magma into an open tunnel (drift) at the Yucca Mountain repository provides insight into proposed scenarios that include the development of secondary pathways to the Earth's surface. Addressing volcanic risk within a decision
Probability model for estimating colorectal polyp progression rates.
Gopalappa, Chaitra; Aydogan-Cremaschi, Selen; Das, Tapas K; Orcun, Seza
2011-03-01
According to the American Cancer Society, colorectal cancer (CRC) is the third most common cause of cancer related deaths in the United States. Experts estimate that about 85% of CRCs begin as precancerous polyps, early detection and treatment of which can significantly reduce the risk of CRC. Hence, it is imperative to develop population-wide intervention strategies for early detection of polyps. Development of such strategies requires precise values of population-specific rates of incidence of polyp and its progression to cancerous stage. There has been a considerable amount of research in recent years on developing screening based CRC intervention strategies. However, these are not supported by population-specific mathematical estimates of progression rates. This paper addresses this need by developing a probability model that estimates polyp progression rates considering race and family history of CRC; note that, it is ethically infeasible to obtain polyp progression rates through clinical trials. We use the estimated rates to simulate the progression of polyps in the population of the State of Indiana, and also the population of a clinical trial conducted in the State of Minnesota, which was obtained from literature. The results from the simulations are used to validate the probability model.
A comparison of tail probability estimators for flood frequency analysis
NASA Astrophysics Data System (ADS)
Moon, Young-Il; Lall, Upmanu; Bosworth, Ken
1993-11-01
Selected techniques for estimating exceedance frequencies of annual maximum flood events at a gaged site are compared in this paper. Four tail probability estimators proposed by Hill (PT1), Hosking and Wallis (PT2) and by Breiman and Stone (ET and QT), and a variable kernel distribution function estimator (VK-C-AC) were compared for three situations — Gaussian data, skewed data (three-parameter gamma) and Gaussian mixture data. The performance of these estimators was compared with method of moment estimates of tail probabilities, using the Gaussian, Pearson Type III, and extreme value distributions. Since the results of the tail probability estimators (PT1, PT2, ET, QT) varied according to the situation, it is not easy to say which tail probability estimator is the best. However, the performance of the variable kernel estimator was relatively consistent across the estimation situations considered in terms of bias and r.m.s.e.
Estimating Radiogenic Cancer Risks
This document presents a revised methodology for EPA's estimation of cancer risks due to low-LET radiation exposures developed in light of information that has become available, especially new information on the Japanese atomic bomb survivors.
Fisher classifier and its probability of error estimation
NASA Technical Reports Server (NTRS)
Chittineni, C. B.
1979-01-01
Computationally efficient expressions are derived for estimating the probability of error using the leave-one-out method. The optimal threshold for the classification of patterns projected onto Fisher's direction is derived. A simple generalization of the Fisher classifier to multiple classes is presented. Computational expressions are developed for estimating the probability of error of the multiclass Fisher classifier.
A new method for estimating extreme rainfall probabilities
Harper, G.A.; O'Hara, T.F. ); Morris, D.I. )
1994-02-01
As part of an EPRI-funded research program, the Yankee Atomic Electric Company developed a new method for estimating probabilities of extreme rainfall. It can be used, along with other techniques, to improve the estimation of probable maximum precipitation values for specific basins or regions.
The Estimation of Tree Posterior Probabilities Using Conditional Clade Probability Distributions
Larget, Bret
2013-01-01
In this article I introduce the idea of conditional independence of separated subtrees as a principle by which to estimate the posterior probability of trees using conditional clade probability distributions rather than simple sample relative frequencies. I describe an algorithm for these calculations and software which implements these ideas. I show that these alternative calculations are very similar to simple sample relative frequencies for high probability trees but are substantially more accurate for relatively low probability trees. The method allows the posterior probability of unsampled trees to be calculated when these trees contain only clades that are in other sampled trees. Furthermore, the method can be used to estimate the total probability of the set of sampled trees which provides a measure of the thoroughness of a posterior sample. [Bayesian phylogenetics; conditional clade distributions; improved accuracy; posterior probabilities of trees.] PMID:23479066
Estimating the probability for major gene Alzheimer disease
Farrer, L.A. Boston Univ. School of Public Health, Boston, MA ); Cupples, L.A. )
1994-02-01
Alzheimer disease (AD) is a neuropsychiatric illness caused by multiple etiologies. Prediction of whether AD is genetically based in a given family is problematic because of censoring bias among unaffected relatives as a consequence of the late onset of the disorder, diagnostic uncertainties, heterogeneity, and limited information in a single family. The authors have developed a method based on Bayesian probability to compute values for a continuous variable that ranks AD families as having a major gene form of AD (MGAD). In addition, they have compared the Bayesian method with a maximum-likelihood approach. These methods incorporate sex- and age-adjusted risk estimates and allow for phenocopies and familial clustering of age on onset. Agreement is high between the two approaches for ranking families as MGAD (Spearman rank [r] = .92). When either method is used, the numerical outcomes are sensitive to assumptions of the gene frequency and cumulative incidence of the disease in the population. Consequently, risk estimates should be used cautiously for counseling purposes; however, there are numerous valid applications of these procedures in genetic and epidemiological studies. 41 refs., 4 figs., 3 tabs.
Bayes estimate of the probability of exceedance of annual floods
NASA Astrophysics Data System (ADS)
Lye, L. M.
1990-03-01
In this paper Lindley's Bayesian approximation procedure is used to obtain the Bayes estimate of the probability of exceedence of a flood discharge. The Bayes estimates of the probability of exceedence has been shown by S.K. Sinha to be equivalent to the estimate of the probability of exceedence from the predictive or Bayesian disribution, of a future flood discharge. The evaluation of complex ratios of multiple integrals common in a Bayesian analysis is not necessary using Lindley's procedure. The Bayes estimates are compared to those obtained by the method of maximum likelihood and the method of moments. The results show that Bayes estimates of the probability of exceedence are larger as expected, but have smaller posterior standard deviations.
Injury Risk Estimation Expertise
Petushek, Erich J.; Ward, Paul; Cokely, Edward T.; Myer, Gregory D.
2015-01-01
Background: Simple observational assessment of movement is a potentially low-cost method for anterior cruciate ligament (ACL) injury screening and prevention. Although many individuals utilize some form of observational assessment of movement, there are currently no substantial data on group skill differences in observational screening of ACL injury risk. Purpose/Hypothesis: The purpose of this study was to compare various groups’ abilities to visually assess ACL injury risk as well as the associated strategies and ACL knowledge levels. The hypothesis was that sports medicine professionals would perform better than coaches and exercise science academics/students and that these subgroups would all perform better than parents and other general population members. Study Design: Cross-sectional study; Level of evidence, 3. Methods: A total of 428 individuals, including physicians, physical therapists, athletic trainers, strength and conditioning coaches, exercise science researchers/students, athletes, parents, and members of the general public participated in the study. Participants completed the ACL Injury Risk Estimation Quiz (ACL-IQ) and answered questions related to assessment strategy and ACL knowledge. Results: Strength and conditioning coaches, athletic trainers, physical therapists, and exercise science students exhibited consistently superior ACL injury risk estimation ability (+2 SD) as compared with sport coaches, parents of athletes, and members of the general public. The performance of a substantial number of individuals in the exercise sciences/sports medicines (approximately 40%) was similar to or exceeded clinical instrument-based biomechanical assessment methods (eg, ACL nomogram). Parents, sport coaches, and the general public had lower ACL-IQ, likely due to their lower ACL knowledge and to rating the importance of knee/thigh motion lower and weight and jump height higher. Conclusion: Substantial cross-professional/group differences in visual ACL
Naive Probability: Model-Based Estimates of Unique Events.
Khemlani, Sangeet S; Lotstein, Max; Johnson-Laird, Philip N
2015-08-01
We describe a dual-process theory of how individuals estimate the probabilities of unique events, such as Hillary Clinton becoming U.S. President. It postulates that uncertainty is a guide to improbability. In its computer implementation, an intuitive system 1 simulates evidence in mental models and forms analog non-numerical representations of the magnitude of degrees of belief. This system has minimal computational power and combines evidence using a small repertoire of primitive operations. It resolves the uncertainty of divergent evidence for single events, for conjunctions of events, and for inclusive disjunctions of events, by taking a primitive average of non-numerical probabilities. It computes conditional probabilities in a tractable way, treating the given event as evidence that may be relevant to the probability of the dependent event. A deliberative system 2 maps the resulting representations into numerical probabilities. With access to working memory, it carries out arithmetical operations in combining numerical estimates. Experiments corroborated the theory's predictions. Participants concurred in estimates of real possibilities. They violated the complete joint probability distribution in the predicted ways, when they made estimates about conjunctions: P(A), P(B), P(A and B), disjunctions: P(A), P(B), P(A or B or both), and conditional probabilities P(A), P(B), P(B|A). They were faster to estimate the probabilities of compound propositions when they had already estimated the probabilities of each of their components. We discuss the implications of these results for theories of probabilistic reasoning.
Estimating the probability of failure when testing reveals no failures
NASA Technical Reports Server (NTRS)
Miller, Keith W.; Morell, Larry J.; Noonan, Robert E.; Park, Stephen K.; Nicol, David M.; Murrill, Branson W.; Voas, Jeffrey M.
1992-01-01
Formulas for estimating the probability of failure when testing reveals no errors are introduced. These formulas incorporate random testing results, information about the input distribution, and prior assumptions about the probability of failure of the software. The formulas are not restricted to equally likely input distributions, and the probability of failure estimate can be adjusted when assumptions about the input distribution change. The formulas are based on a discrete sample space statistical model of software and include Bayesian prior assumptions. Reusable software and software in life-critical applications are particularly appropriate candidates for this type of analysis.
27% Probable: Estimating Whether or Not Large Numbers Are Prime.
ERIC Educational Resources Information Center
Bosse, Michael J.
2001-01-01
This brief investigation exemplifies such considerations by relating concepts from number theory, set theory, probability, logic, and calculus. Satisfying the call for students to acquire skills in estimation, the following technique allows one to "immediately estimate" whether or not a number is prime. (MM)
Nonparametric probability density estimation by optimization theoretic techniques
NASA Technical Reports Server (NTRS)
Scott, D. W.
1976-01-01
Two nonparametric probability density estimators are considered. The first is the kernel estimator. The problem of choosing the kernel scaling factor based solely on a random sample is addressed. An interactive mode is discussed and an algorithm proposed to choose the scaling factor automatically. The second nonparametric probability estimate uses penalty function techniques with the maximum likelihood criterion. A discrete maximum penalized likelihood estimator is proposed and is shown to be consistent in the mean square error. A numerical implementation technique for the discrete solution is discussed and examples displayed. An extensive simulation study compares the integrated mean square error of the discrete and kernel estimators. The robustness of the discrete estimator is demonstrated graphically.
Low-probability flood risk modeling for New York City.
Aerts, Jeroen C J H; Lin, Ning; Botzen, Wouter; Emanuel, Kerry; de Moel, Hans
2013-05-01
The devastating impact by Hurricane Sandy (2012) again showed New York City (NYC) is one of the most vulnerable cities to coastal flooding around the globe. The low-lying areas in NYC can be flooded by nor'easter storms and North Atlantic hurricanes. The few studies that have estimated potential flood damage for NYC base their damage estimates on only a single, or a few, possible flood events. The objective of this study is to assess the full distribution of hurricane flood risk in NYC. This is done by calculating potential flood damage with a flood damage model that uses many possible storms and surge heights as input. These storms are representative for the low-probability/high-impact flood hazard faced by the city. Exceedance probability-loss curves are constructed under different assumptions about the severity of flood damage. The estimated flood damage to buildings for NYC is between US$59 and 129 millions/year. The damage caused by a 1/100-year storm surge is within a range of US$2 bn-5 bn, while this is between US$5 bn and 11 bn for a 1/500-year storm surge. An analysis of flood risk in each of the five boroughs of NYC finds that Brooklyn and Queens are the most vulnerable to flooding. This study examines several uncertainties in the various steps of the risk analysis, which resulted in variations in flood damage estimations. These uncertainties include: the interpolation of flood depths; the use of different flood damage curves; and the influence of the spectra of characteristics of the simulated hurricanes.
Local estimation of posterior class probabilities to minimize classification errors.
Guerrero-Curieses, Alicia; Cid-Sueiro, Jesús; Alaiz-Rodríguez, Rocío; Figueiras-Vidal, Aníbal R
2004-03-01
Decision theory shows that the optimal decision is a function of the posterior class probabilities. More specifically, in binary classification, the optimal decision is based on the comparison of the posterior probabilities with some threshold. Therefore, the most accurate estimates of the posterior probabilities are required near these decision thresholds. This paper discusses the design of objective functions that provide more accurate estimates of the probability values, taking into account the characteristics of each decision problem. We propose learning algorithms based on the stochastic gradient minimization of these loss functions. We show that the performance of the classifier is improved when these algorithms behave like sample selectors: samples near the decision boundary are the most relevant during learning.
Estimation of transition probabilities of credit ratings for several companies
NASA Astrophysics Data System (ADS)
Peng, Gan Chew; Hin, Pooi Ah
2016-10-01
This paper attempts to estimate the transition probabilities of credit ratings for a number of companies whose ratings have a dependence structure. Binary codes are used to represent the index of a company together with its ratings in the present and next quarters. We initially fit the data on the vector of binary codes with a multivariate power-normal distribution. We next compute the multivariate conditional distribution for the binary codes of rating in the next quarter when the index of the company and binary codes of the company in the present quarter are given. From the conditional distribution, we compute the transition probabilities of the company's credit ratings in two consecutive quarters. The resulting transition probabilities tally fairly well with the maximum likelihood estimates for the time-independent transition probabilities.
Estimating the empirical probability of submarine landslide occurrence
Geist, Eric L.; Parsons, Thomas E.; Mosher, David C.; Shipp, Craig; Moscardelli, Lorena; Chaytor, Jason D.; Baxter, Christopher D. P.; Lee, Homa J.; Urgeles, Roger
2010-01-01
The empirical probability for the occurrence of submarine landslides at a given location can be estimated from age dates of past landslides. In this study, tools developed to estimate earthquake probability from paleoseismic horizons are adapted to estimate submarine landslide probability. In both types of estimates, one has to account for the uncertainty associated with age-dating individual events as well as the open time intervals before and after the observed sequence of landslides. For observed sequences of submarine landslides, we typically only have the age date of the youngest event and possibly of a seismic horizon that lies below the oldest event in a landslide sequence. We use an empirical Bayes analysis based on the Poisson-Gamma conjugate prior model specifically applied to the landslide probability problem. This model assumes that landslide events as imaged in geophysical data are independent and occur in time according to a Poisson distribution characterized by a rate parameter λ. With this method, we are able to estimate the most likely value of λ and, importantly, the range of uncertainty in this estimate. Examples considered include landslide sequences observed in the Santa Barbara Channel, California, and in Port Valdez, Alaska. We confirm that given the uncertainties of age dating that landslide complexes can be treated as single events by performing statistical test of age dates representing the main failure episode of the Holocene Storegga landslide complex.
Estimation of State Transition Probabilities: A Neural Network Model
NASA Astrophysics Data System (ADS)
Saito, Hiroshi; Takiyama, Ken; Okada, Masato
2015-12-01
Humans and animals can predict future states on the basis of acquired knowledge. This prediction of the state transition is important for choosing the best action, and the prediction is only possible if the state transition probability has already been learned. However, how our brains learn the state transition probability is unknown. Here, we propose a simple algorithm for estimating the state transition probability by utilizing the state prediction error. We analytically and numerically confirmed that our algorithm is able to learn the probability completely with an appropriate learning rate. Furthermore, our learning rule reproduced experimentally reported psychometric functions and neural activities in the lateral intraparietal area in a decision-making task. Thus, our algorithm might describe the manner in which our brains learn state transition probabilities and predict future states.
An application of recurrent nets to phone probability estimation.
Robinson, A J
1994-01-01
This paper presents an application of recurrent networks for phone probability estimation in large vocabulary speech recognition. The need for efficient exploitation of context information is discussed; a role for which the recurrent net appears suitable. An overview of early developments of recurrent nets for phone recognition is given along with the more recent improvements that include their integration with Markov models. Recognition results are presented for the DARPA TIMIT and Resource Management tasks, and it is concluded that recurrent nets are competitive with traditional means for performing phone probability estimation.
Expected probability weighted moment estimator for censored flood data
NASA Astrophysics Data System (ADS)
Jeon, Jong-June; Kim, Young-Oh; Kim, Yongdai
2011-08-01
Two well-known methods for estimating statistical distributions in hydrology are the Method of Moments (MOMs) and the method of probability weighted moments (PWM). This paper is concerned with the case where a part of the sample is censored. One situation where this might occur is when systematic data (e.g. from gauges) are combined with historical data, since the latter are often only reported if they exceed a high threshold. For this problem, three previously derived estimators are the "B17B" estimator, which is a direct modification of MOM to allow for partial censoring; the "partial PWM estimator", which similarly modifies PWM; and the "expected moments algorithm" estimator, which improves on B17B by replacing a sample adjustment of the censored-data moments with a population adjustment. The present paper proposes a similar modification to the PWM estimator, resulting in the "expected probability weighted moments (EPWM)" estimator. Simulation comparisons of these four estimators and also the maximum likelihood estimator show that the EPWM method is at least competitive with the other four and in many cases the best of the five estimators.
Improving estimates of tree mortality probability using potential growth rate
Das, Adrian J.; Stephenson, Nathan L.
2015-01-01
Tree growth rate is frequently used to estimate mortality probability. Yet, growth metrics can vary in form, and the justification for using one over another is rarely clear. We tested whether a growth index (GI) that scales the realized diameter growth rate against the potential diameter growth rate (PDGR) would give better estimates of mortality probability than other measures. We also tested whether PDGR, being a function of tree size, might better correlate with the baseline mortality probability than direct measurements of size such as diameter or basal area. Using a long-term dataset from the Sierra Nevada, California, U.S.A., as well as existing species-specific estimates of PDGR, we developed growth–mortality models for four common species. For three of the four species, models that included GI, PDGR, or a combination of GI and PDGR were substantially better than models without them. For the fourth species, the models including GI and PDGR performed roughly as well as a model that included only the diameter growth rate. Our results suggest that using PDGR can improve our ability to estimate tree survival probability. However, in the absence of PDGR estimates, the diameter growth rate was the best empirical predictor of mortality, in contrast to assumptions often made in the literature.
Probability Estimation of CO2 Leakage Through Faults at Geologic Carbon Sequestration Sites
Zhang, Yingqi; Oldenburg, Curt; Finsterle, Stefan; Jordan, Preston; Zhang, Keni
2008-11-01
Leakage of CO{sub 2} and brine along faults at geologic carbon sequestration (GCS) sites is a primary concern for storage integrity. The focus of this study is on the estimation of the probability of leakage along faults or fractures. This leakage probability is controlled by the probability of a connected network of conduits existing at a given site, the probability of this network encountering the CO{sub 2} plume, and the probability of this network intersecting environmental resources that may be impacted by leakage. This work is designed to fit into a risk assessment and certification framework that uses compartments to represent vulnerable resources such as potable groundwater, health and safety, and the near-surface environment. The method we propose includes using percolation theory to estimate the connectivity of the faults, and generating fuzzy rules from discrete fracture network simulations to estimate leakage probability. By this approach, the probability of CO{sub 2} escaping into a compartment for a given system can be inferred from the fuzzy rules. The proposed method provides a quick way of estimating the probability of CO{sub 2} or brine leaking into a compartment. In addition, it provides the uncertainty range of the estimated probability.
Using Correlation to Compute Better Probability Estimates in Plan Graphs
NASA Technical Reports Server (NTRS)
Bryce, Daniel; Smith, David E.
2006-01-01
Plan graphs are commonly used in planning to help compute heuristic "distance" estimates between states and goals. A few authors have also attempted to use plan graphs in probabilistic planning to compute estimates of the probability that propositions can be achieved and actions can be performed. This is done by propagating probability information forward through the plan graph from the initial conditions through each possible action to the action effects, and hence to the propositions at the next layer of the plan graph. The problem with these calculations is that they make very strong independence assumptions - in particular, they usually assume that the preconditions for each action are independent of each other. This can lead to gross overestimates in probability when the plans for those preconditions interfere with each other. It can also lead to gross underestimates of probability when there is synergy between the plans for two or more preconditions. In this paper we introduce a notion of the binary correlation between two propositions and actions within a plan graph, show how to propagate this information within a plan graph, and show how this improves probability estimates for planning. This notion of correlation can be thought of as a continuous generalization of the notion of mutual exclusion (mutex) often used in plan graphs. At one extreme (correlation=0) two propositions or actions are completely mutex. With correlation = 1, two propositions or actions are independent, and with correlation > 1, two propositions or actions are synergistic. Intermediate values can and do occur indicating different degrees to which propositions and action interfere or are synergistic. We compare this approach with another recent approach by Bryce that computes probability estimates using Monte Carlo simulation of possible worlds in plan graphs.
Recursive estimation of prior probabilities using the mixture approach
NASA Technical Reports Server (NTRS)
Kazakos, D.
1974-01-01
The problem of estimating the prior probabilities q sub k of a mixture of known density functions f sub k(X), based on a sequence of N statistically independent observations is considered. It is shown that for very mild restrictions on f sub k(X), the maximum likelihood estimate of Q is asymptotically efficient. A recursive algorithm for estimating Q is proposed, analyzed, and optimized. For the M = 2 case, it is possible for the recursive algorithm to achieve the same performance with the maximum likelihood one. For M 2, slightly inferior performance is the price for having a recursive algorithm. However, the loss is computable and tolerable.
Methods for estimating drought streamflow probabilities for Virginia streams
Austin, Samuel H.
2014-01-01
Maximum likelihood logistic regression model equations used to estimate drought flow probabilities for Virginia streams are presented for 259 hydrologic basins in Virginia. Winter streamflows were used to estimate the likelihood of streamflows during the subsequent drought-prone summer months. The maximum likelihood logistic regression models identify probable streamflows from 5 to 8 months in advance. More than 5 million streamflow daily values collected over the period of record (January 1, 1900 through May 16, 2012) were compiled and analyzed over a minimum 10-year (maximum 112-year) period of record. The analysis yielded the 46,704 equations with statistically significant fit statistics and parameter ranges published in two tables in this report. These model equations produce summer month (July, August, and September) drought flow threshold probabilities as a function of streamflows during the previous winter months (November, December, January, and February). Example calculations are provided, demonstrating how to use the equations to estimate probable streamflows as much as 8 months in advance.
Estimating transition probabilities in unmarked populations --entropy revisited
Cooch, E.G.; Link, W.A.
1999-01-01
The probability of surviving and moving between 'states' is of great interest to biologists. Robust estimation of these transitions using multiple observations of individually identifiable marked individuals has received considerable attention in recent years. However, in some situations, individuals are not identifiable (or have a very low recapture rate), although all individuals in a sample can be assigned to a particular state (e.g. breeding or non-breeding) without error. In such cases, only aggregate data (number of individuals in a given state at each occasion) are available. If the underlying matrix of transition probabilities does not vary through time and aggregate data are available for several time periods, then it is possible to estimate these parameters using least-squares methods. Even when such data are available, this assumption of stationarity will usually be deemed overly restrictive and, frequently, data will only be available for two time periods. In these cases, the problem reduces to estimating the most likely matrix (or matrices) leading to the observed frequency distribution of individuals in each state. An entropy maximization approach has been previously suggested. In this paper, we show that the entropy approach rests on a particular limiting assumption, and does not provide estimates of latent population parameters (the transition probabilities), but rather predictions of realized rates.
On estimating the fracture probability of nuclear graphite components
NASA Astrophysics Data System (ADS)
Srinivasan, Makuteswara
2008-10-01
The properties of nuclear grade graphites exhibit anisotropy and could vary considerably within a manufactured block. Graphite strength is affected by the direction of alignment of the constituent coke particles, which is dictated by the forming method, coke particle size, and the size, shape, and orientation distribution of pores in the structure. In this paper, a Weibull failure probability analysis for components is presented using the American Society of Testing Materials strength specification for nuclear grade graphites for core components in advanced high-temperature gas-cooled reactors. The risk of rupture (probability of fracture) and survival probability (reliability) of large graphite blocks are calculated for varying and discrete values of service tensile stresses. The limitations in these calculations are discussed from considerations of actual reactor environmental conditions that could potentially degrade the specification properties because of damage due to complex interactions between irradiation, temperature, stress, and variability in reactor operation.
Collective animal behavior from Bayesian estimation and probability matching.
Pérez-Escudero, Alfonso; de Polavieja, Gonzalo G
2011-11-01
Animals living in groups make movement decisions that depend, among other factors, on social interactions with other group members. Our present understanding of social rules in animal collectives is mainly based on empirical fits to observations, with less emphasis in obtaining first-principles approaches that allow their derivation. Here we show that patterns of collective decisions can be derived from the basic ability of animals to make probabilistic estimations in the presence of uncertainty. We build a decision-making model with two stages: Bayesian estimation and probabilistic matching. In the first stage, each animal makes a Bayesian estimation of which behavior is best to perform taking into account personal information about the environment and social information collected by observing the behaviors of other animals. In the probability matching stage, each animal chooses a behavior with a probability equal to the Bayesian-estimated probability that this behavior is the most appropriate one. This model derives very simple rules of interaction in animal collectives that depend only on two types of reliability parameters, one that each animal assigns to the other animals and another given by the quality of the non-social information. We test our model by obtaining theoretically a rich set of observed collective patterns of decisions in three-spined sticklebacks, Gasterosteus aculeatus, a shoaling fish species. The quantitative link shown between probabilistic estimation and collective rules of behavior allows a better contact with other fields such as foraging, mate selection, neurobiology and psychology, and gives predictions for experiments directly testing the relationship between estimation and collective behavior.
Estimating the exceedance probability of rain rate by logistic regression
NASA Technical Reports Server (NTRS)
Chiu, Long S.; Kedem, Benjamin
1990-01-01
Recent studies have shown that the fraction of an area with rain intensity above a fixed threshold is highly correlated with the area-averaged rain rate. To estimate the fractional rainy area, a logistic regression model, which estimates the conditional probability that rain rate over an area exceeds a fixed threshold given the values of related covariates, is developed. The problem of dependency in the data in the estimation procedure is bypassed by the method of partial likelihood. Analyses of simulated scanning multichannel microwave radiometer and observed electrically scanning microwave radiometer data during the Global Atlantic Tropical Experiment period show that the use of logistic regression in pixel classification is superior to multiple regression in predicting whether rain rate at each pixel exceeds a given threshold, even in the presence of noisy data. The potential of the logistic regression technique in satellite rain rate estimation is discussed.
New method for estimating low-earth-orbit collision probabilities
NASA Technical Reports Server (NTRS)
Vedder, John D.; Tabor, Jill L.
1991-01-01
An unconventional but general method is described for estimating the probability of collision between an earth-orbiting spacecraft and orbital debris. This method uses a Monte Caralo simulation of the orbital motion of the target spacecraft and each discrete debris object to generate an empirical set of distances, each distance representing the separation between the spacecraft and the nearest debris object at random times. Using concepts from the asymptotic theory of extreme order statistics, an analytical density function is fitted to this set of minimum distances. From this function, it is possible to generate realistic collision estimates for the spacecraft.
Estimating probable flaw distributions in PWR steam generator tubes
Gorman, J.A.; Turner, A.P.L.
1997-02-01
This paper describes methods for estimating the number and size distributions of flaws of various types in PWR steam generator tubes. These estimates are needed when calculating the probable primary to secondary leakage through steam generator tubes under postulated accidents such as severe core accidents and steam line breaks. The paper describes methods for two types of predictions: (1) the numbers of tubes with detectable flaws of various types as a function of time, and (2) the distributions in size of these flaws. Results are provided for hypothetical severely affected, moderately affected and lightly affected units. Discussion is provided regarding uncertainties and assumptions in the data and analyses.
Conditional Probability Density Functions Arising in Bearing Estimation
1994-05-01
and a better known performance measure: the Cramer-Rao bound . 14. SUMECT TEm IL5 NUlMN OF PAMES Probability Density Function, bearing angle estimation...results obtained using the calculated density functions and a better known performance measure: the Cramer-Rao bound . The major results obtained are as...48 15. Sampling Inteval , Propagation Delay, and Covariance Singularities ....... 52 viii List of Figures (continued
Probability Density and CFAR Threshold Estimation for Hyperspectral Imaging
Clark, G A
2004-09-21
The work reported here shows the proof of principle (using a small data set) for a suite of algorithms designed to estimate the probability density function of hyperspectral background data and compute the appropriate Constant False Alarm Rate (CFAR) matched filter decision threshold for a chemical plume detector. Future work will provide a thorough demonstration of the algorithms and their performance with a large data set. The LASI (Large Aperture Search Initiative) Project involves instrumentation and image processing for hyperspectral images of chemical plumes in the atmosphere. The work reported here involves research and development on algorithms for reducing the false alarm rate in chemical plume detection and identification algorithms operating on hyperspectral image cubes. The chemical plume detection algorithms to date have used matched filters designed using generalized maximum likelihood ratio hypothesis testing algorithms [1, 2, 5, 6, 7, 12, 10, 11, 13]. One of the key challenges in hyperspectral imaging research is the high false alarm rate that often results from the plume detector [1, 2]. The overall goal of this work is to extend the classical matched filter detector to apply Constant False Alarm Rate (CFAR) methods to reduce the false alarm rate, or Probability of False Alarm P{sub FA} of the matched filter [4, 8, 9, 12]. A detector designer is interested in minimizing the probability of false alarm while simultaneously maximizing the probability of detection P{sub D}. This is summarized by the Receiver Operating Characteristic Curve (ROC) [10, 11], which is actually a family of curves depicting P{sub D} vs. P{sub FA}parameterized by varying levels of signal to noise (or clutter) ratio (SNR or SCR). Often, it is advantageous to be able to specify a desired P{sub FA} and develop a ROC curve (P{sub D} vs. decision threshold r{sub 0}) for that case. That is the purpose of this work. Specifically, this work develops a set of algorithms and MATLAB
Estimation of the probability of success in petroleum exploration
Davis, J.C.
1977-01-01
A probabilistic model for oil exploration can be developed by assessing the conditional relationship between perceived geologic variables and the subsequent discovery of petroleum. Such a model includes two probabilistic components, the first reflecting the association between a geologic condition (structural closure, for example) and the occurrence of oil, and the second reflecting the uncertainty associated with the estimation of geologic variables in areas of limited control. Estimates of the conditional relationship between geologic variables and subsequent production can be found by analyzing the exploration history of a "training area" judged to be geologically similar to the exploration area. The geologic variables are assessed over the training area using an historical subset of the available data, whose density corresponds to the present control density in the exploration area. The success or failure of wells drilled in the training area subsequent to the time corresponding to the historical subset provides empirical estimates of the probability of success conditional upon geology. Uncertainty in perception of geological conditions may be estimated from the distribution of errors made in geologic assessment using the historical subset of control wells. These errors may be expressed as a linear function of distance from available control. Alternatively, the uncertainty may be found by calculating the semivariogram of the geologic variables used in the analysis: the two procedures will yield approximately equivalent results. The empirical probability functions may then be transferred to the exploration area and used to estimate the likelihood of success of specific exploration plays. These estimates will reflect both the conditional relationship between the geological variables used to guide exploration and the uncertainty resulting from lack of control. The technique is illustrated with case histories from the mid-Continent area of the U.S.A. ?? 1977 Plenum
Estimation of probability densities using scale-free field theories.
Kinney, Justin B
2014-07-01
The question of how best to estimate a continuous probability density from finite data is an intriguing open problem at the interface of statistics and physics. Previous work has argued that this problem can be addressed in a natural way using methods from statistical field theory. Here I describe results that allow this field-theoretic approach to be rapidly and deterministically computed in low dimensions, making it practical for use in day-to-day data analysis. Importantly, this approach does not impose a privileged length scale for smoothness of the inferred probability density, but rather learns a natural length scale from the data due to the tradeoff between goodness of fit and an Occam factor. Open source software implementing this method in one and two dimensions is provided.
Cost functions to estimate a posteriori probabilities in multiclass problems.
Cid-Sueiro, J; Arribas, J I; Urbán-Muñoz, S; Figueiras-Vidal, A R
1999-01-01
The problem of designing cost functions to estimate a posteriori probabilities in multiclass problems is addressed in this paper. We establish necessary and sufficient conditions that these costs must satisfy in one-class one-output networks whose outputs are consistent with probability laws. We focus our attention on a particular subset of the corresponding cost functions; those which verify two usually interesting properties: symmetry and separability (well-known cost functions, such as the quadratic cost or the cross entropy are particular cases in this subset). Finally, we present a universal stochastic gradient learning rule for single-layer networks, in the sense of minimizing a general version of these cost functions for a wide family of nonlinear activation functions.
Estimation of probability densities using scale-free field theories
NASA Astrophysics Data System (ADS)
Kinney, Justin B.
2014-07-01
The question of how best to estimate a continuous probability density from finite data is an intriguing open problem at the interface of statistics and physics. Previous work has argued that this problem can be addressed in a natural way using methods from statistical field theory. Here I describe results that allow this field-theoretic approach to be rapidly and deterministically computed in low dimensions, making it practical for use in day-to-day data analysis. Importantly, this approach does not impose a privileged length scale for smoothness of the inferred probability density, but rather learns a natural length scale from the data due to the tradeoff between goodness of fit and an Occam factor. Open source software implementing this method in one and two dimensions is provided.
Probability Distribution Estimation for Autoregressive Pixel-Predictive Image Coding.
Weinlich, Andreas; Amon, Peter; Hutter, Andreas; Kaup, André
2016-03-01
Pixelwise linear prediction using backward-adaptive least-squares or weighted least-squares estimation of prediction coefficients is currently among the state-of-the-art methods for lossless image compression. While current research is focused on mean intensity prediction of the pixel to be transmitted, best compression requires occurrence probability estimates for all possible intensity values. Apart from common heuristic approaches, we show how prediction error variance estimates can be derived from the (weighted) least-squares training region and how a complete probability distribution can be built based on an autoregressive image model. The analysis of image stationarity properties further allows deriving a novel formula for weight computation in weighted least-squares proofing and generalizing ad hoc equations from the literature. For sparse intensity distributions in non-natural images, a modified image model is presented. Evaluations were done in the newly developed C++ framework volumetric, artificial, and natural image lossless coder (Vanilc), which can compress a wide range of images, including 16-bit medical 3D volumes or multichannel data. A comparison with several of the best available lossless image codecs proofs that the method can achieve very competitive compression ratios. In terms of reproducible research, the source code of Vanilc has been made public.
Estimating transition probabilities among everglades wetland communities using multistate models
Hotaling, A.S.; Martin, J.; Kitchens, W.M.
2009-01-01
In this study we were able to provide the first estimates of transition probabilities of wet prairie and slough vegetative communities in Water Conservation Area 3A (WCA3A) of the Florida Everglades and to identify the hydrologic variables that determine these transitions. These estimates can be used in management models aimed at restoring proportions of wet prairie and slough habitats to historical levels in the Everglades. To determine what was driving the transitions between wet prairie and slough communities we evaluated three hypotheses: seasonality, impoundment, and wet and dry year cycles using likelihood-based multistate models to determine the main driver of wet prairie conversion in WCA3A. The most parsimonious model included the effect of wet and dry year cycles on vegetative community conversions. Several ecologists have noted wet prairie conversion in southern WCA3A but these are the first estimates of transition probabilities among these community types. In addition, to being useful for management of the Everglades we believe that our framework can be used to address management questions in other ecosystems. ?? 2009 The Society of Wetland Scientists.
Classifier calibration using splined empirical probabilities in clinical risk prediction.
Gaudoin, René; Montana, Giovanni; Jones, Simon; Aylin, Paul; Bottle, Alex
2015-06-01
The aims of supervised machine learning (ML) applications fall into three broad categories: classification, ranking, and calibration/probability estimation. Many ML methods and evaluation techniques relate to the first two. Nevertheless, there are many applications where having an accurate probability estimate is of great importance. Deriving accurate probabilities from the output of a ML method is therefore an active area of research, resulting in several methods to turn a ranking into class probability estimates. In this manuscript we present a method, splined empirical probabilities, based on the receiver operating characteristic (ROC) to complement existing algorithms such as isotonic regression. Unlike most other methods it works with a cumulative quantity, the ROC curve, and as such can be tagged onto an ROC analysis with minor effort. On a diverse set of measures of the quality of probability estimates (Hosmer-Lemeshow, Kullback-Leibler divergence, differences in the cumulative distribution function) using simulated and real health care data, our approach compares favourably with the standard calibration method, the pool adjacent violators algorithm used to perform isotonic regression.
Site Specific Probable Maximum Precipitation Estimates and Professional Judgement
NASA Astrophysics Data System (ADS)
Hayes, B. D.; Kao, S. C.; Kanney, J. F.; Quinlan, K. R.; DeNeale, S. T.
2015-12-01
State and federal regulatory authorities currently rely upon the US National Weather Service Hydrometeorological Reports (HMRs) to determine probable maximum precipitation (PMP) estimates (i.e., rainfall depths and durations) for estimating flooding hazards for relatively broad regions in the US. PMP estimates for the contributing watersheds upstream of vulnerable facilities are used to estimate riverine flooding hazards while site-specific estimates for small water sheds are appropriate for individual facilities such as nuclear power plants. The HMRs are often criticized due to their limitations on basin size, questionable applicability in regions affected by orographic effects, their lack of consist methods, and generally by their age. HMR-51 for generalized PMP estimates for the United States east of the 105th meridian, was published in 1978 and is sometimes perceived as overly conservative. The US Nuclear Regulatory Commission (NRC), is currently reviewing several flood hazard evaluation reports that rely on site specific PMP estimates that have been commercially developed. As such, NRC has recently investigated key areas of expert judgement via a generic audit and one in-depth site specific review as they relate to identifying and quantifying actual and potential storm moisture sources, determining storm transposition limits, and adjusting available moisture during storm transposition. Though much of the approach reviewed was considered a logical extension of HMRs, two key points of expert judgement stood out for further in-depth review. The first relates primarily to small storms and the use of a heuristic for storm representative dew point adjustment developed for the Electric Power Research Institute by North American Weather Consultants in 1993 in order to harmonize historic storms for which only 12 hour dew point data was available with more recent storms in a single database. The second issue relates to the use of climatological averages for spatially
2005-01-01
preparedness by addressing unique planning, equipment, training, and exercise needs of large urban areas (DHS, 2004). Al- though there appears to be agreement ...reasonable minimum standards for community preparedness. Until these questions are answered, allocating home- land security resources based on risk is the...and threats are correlated with population density. There are practical benefits for using simple risk indicators such as those based upon population
Automated estimation of rare event probabilities in biochemical systems
Daigle, Bernie J.; Roh, Min K.; Gillespie, Dan T.; Petzold, Linda R.
2011-01-01
In biochemical systems, the occurrence of a rare event can be accompanied by catastrophic consequences. Precise characterization of these events using Monte Carlo simulation methods is often intractable, as the number of realizations needed to witness even a single rare event can be very large. The weighted stochastic simulation algorithm (wSSA) [J. Chem. Phys. 129, 165101 (2008)] and its subsequent extension [J. Chem. Phys. 130, 174103 (2009)] alleviate this difficulty with importance sampling, which effectively biases the system toward the desired rare event. However, extensive computation coupled with substantial insight into a given system is required, as there is currently no automatic approach for choosing wSSA parameters. We present a novel modification of the wSSA—the doubly weighted SSA (dwSSA)—that makes possible a fully automated parameter selection method. Our approach uses the information-theoretic concept of cross entropy to identify parameter values yielding minimum variance rare event probability estimates. We apply the method to four examples: a pure birth process, a birth-death process, an enzymatic futile cycle, and a yeast polarization model. Our results demonstrate that the proposed method (1) enables probability estimation for a class of rare events that cannot be interrogated with the wSSA, and (2) for all examples tested, reduces the number of runs needed to achieve comparable accuracy by multiple orders of magnitude. For a particular rare event in the yeast polarization model, our method transforms a projected simulation time of 600 years to three hours. Furthermore, by incorporating information-theoretic principles, our approach provides a framework for the development of more sophisticated influencing schemes that should further improve estimation accuracy. PMID:21280690
Lermer, Eva; Streicher, Bernhard; Sachs, Rainer; Raue, Martina; Frey, Dieter
2016-03-01
Recent findings on construal level theory (CLT) suggest that abstract thinking leads to a lower estimated probability of an event occurring compared to concrete thinking. We applied this idea to the risk context and explored the influence of construal level (CL) on the overestimation of small and underestimation of large probabilities for risk estimates concerning a vague target person (Study 1 and Study 3) and personal risk estimates (Study 2). We were specifically interested in whether the often-found overestimation of small probabilities could be reduced with abstract thinking, and the often-found underestimation of large probabilities was reduced with concrete thinking. The results showed that CL influenced risk estimates. In particular, a concrete mindset led to higher risk estimates compared to an abstract mindset for several adverse events, including events with small and large probabilities. This suggests that CL manipulation can indeed be used for improving the accuracy of lay people's estimates of small and large probabilities. Moreover, the results suggest that professional risk managers' risk estimates of common events (thus with a relatively high probability) could be improved by adopting a concrete mindset. However, the abstract manipulation did not lead managers to estimate extremely unlikely events more accurately. Potential reasons for different CL manipulation effects on risk estimates' accuracy between lay people and risk managers are discussed.
Online Reinforcement Learning Using a Probability Density Estimation.
Agostini, Alejandro; Celaya, Enric
2017-01-01
Function approximation in online, incremental, reinforcement learning needs to deal with two fundamental problems: biased sampling and nonstationarity. In this kind of task, biased sampling occurs because samples are obtained from specific trajectories dictated by the dynamics of the environment and are usually concentrated in particular convergence regions, which in the long term tend to dominate the approximation in the less sampled regions. The nonstationarity comes from the recursive nature of the estimations typical of temporal difference methods. This nonstationarity has a local profile, varying not only along the learning process but also along different regions of the state space. We propose to deal with these problems using an estimation of the probability density of samples represented with a gaussian mixture model. To deal with the nonstationarity problem, we use the common approach of introducing a forgetting factor in the updating formula. However, instead of using the same forgetting factor for the whole domain, we make it dependent on the local density of samples, which we use to estimate the nonstationarity of the function at any given input point. To address the biased sampling problem, the forgetting factor applied to each mixture component is modulated according to the new information provided in the updating, rather than forgetting depending only on time, thus avoiding undesired distortions of the approximation in less sampled regions.
Structural Reliability Using Probability Density Estimation Methods Within NESSUS
NASA Technical Reports Server (NTRS)
Chamis, Chrisos C. (Technical Monitor); Godines, Cody Ric
2003-01-01
A reliability analysis studies a mathematical model of a physical system taking into account uncertainties of design variables and common results are estimations of a response density, which also implies estimations of its parameters. Some common density parameters include the mean value, the standard deviation, and specific percentile(s) of the response, which are measures of central tendency, variation, and probability regions, respectively. Reliability analyses are important since the results can lead to different designs by calculating the probability of observing safe responses in each of the proposed designs. All of this is done at the expense of added computational time as compared to a single deterministic analysis which will result in one value of the response out of many that make up the density of the response. Sampling methods, such as monte carlo (MC) and latin hypercube sampling (LHS), can be used to perform reliability analyses and can compute nonlinear response density parameters even if the response is dependent on many random variables. Hence, both methods are very robust; however, they are computationally expensive to use in the estimation of the response density parameters. Both methods are 2 of 13 stochastic methods that are contained within the Numerical Evaluation of Stochastic Structures Under Stress (NESSUS) program. NESSUS is a probabilistic finite element analysis (FEA) program that was developed through funding from NASA Glenn Research Center (GRC). It has the additional capability of being linked to other analysis programs; therefore, probabilistic fluid dynamics, fracture mechanics, and heat transfer are only a few of what is possible with this software. The LHS method is the newest addition to the stochastic methods within NESSUS. Part of this work was to enhance NESSUS with the LHS method. The new LHS module is complete, has been successfully integrated with NESSUS, and been used to study four different test cases that have been
2007-12-01
Implementing Risk Management on Software Intensive Projects. IEEE Software, 14(3):83-89. Fairley , R . (1994). Risk Management for Software Projects...conditional probability and the Bayesian effect is preceded by an introduction to some basic concepts of probability. Though this discussion draws from R ...Engineering Institute, Carnegie Mellon University, Pittsburgh, Pennsylvania 15213, USA. Charette, R . N. (1991). The Risks with Risk Analysis
Impaired probability estimation and decision-making in pathological gambling poker players.
Linnet, Jakob; Frøslev, Mette; Ramsgaard, Stine; Gebauer, Line; Mouridsen, Kim; Wohlert, Victoria
2012-03-01
Poker has gained tremendous popularity in recent years, increasing the risk for some individuals to develop pathological gambling. Here, we investigated cognitive biases in a computerized two-player poker task against a fictive opponent, among 12 pathological gambling poker players (PGP), 10 experienced poker players (ExP), and 11 inexperienced poker players (InP). Players were compared on probability estimation and decision-making with the hypothesis that ExP would have significantly lower cognitive biases than PGP and InP, and that the groups could be differentiated based on their cognitive bias styles. The results showed that ExP had a significantly lower average error margin in probability estimation than PGP and InP, and that PGP played hands with lower winning probability than ExP. Binomial logistic regression showed perfect differentiation (100%) between ExP and PGP, and 90.5% classification accuracy between ExP and InP. Multinomial logistic regression showed an overall classification accuracy of 23 out of 33 (69.7%) between the three groups. The classification accuracy of ExP was higher than that of PGP and InP due to the similarities in probability estimation and decision-making between PGP and InP. These impairments in probability estimation and decision-making of PGP may have implications for assessment and treatment of cognitive biases in pathological gambling poker players.
Exaggerated Risk: Prospect Theory and Probability Weighting in Risky Choice
ERIC Educational Resources Information Center
Kusev, Petko; van Schaik, Paul; Ayton, Peter; Dent, John; Chater, Nick
2009-01-01
In 5 experiments, we studied precautionary decisions in which participants decided whether or not to buy insurance with specified cost against an undesirable event with specified probability and cost. We compared the risks taken for precautionary decisions with those taken for equivalent monetary gambles. Fitting these data to Tversky and…
The estimation of probable maximum precipitation: the case of Catalonia.
Casas, M Carmen; Rodríguez, Raül; Nieto, Raquel; Redaño, Angel
2008-12-01
A brief overview of the different techniques used to estimate the probable maximum precipitation (PMP) is presented. As a particular case, the 1-day PMP over Catalonia has been calculated and mapped with a high spatial resolution. For this purpose, the annual maximum daily rainfall series from 145 pluviometric stations of the Instituto Nacional de Meteorología (Spanish Weather Service) in Catalonia have been analyzed. In order to obtain values of PMP, an enveloping frequency factor curve based on the actual rainfall data of stations in the region has been developed. This enveloping curve has been used to estimate 1-day PMP values of all the 145 stations. Applying the Cressman method, the spatial analysis of these values has been achieved. Monthly precipitation climatological data, obtained from the application of Geographic Information Systems techniques, have been used as the initial field for the analysis. The 1-day PMP at 1 km(2) spatial resolution over Catalonia has been objectively determined, varying from 200 to 550 mm. Structures with wavelength longer than approximately 35 km can be identified and, despite their general concordance, the obtained 1-day PMP spatial distribution shows remarkable differences compared to the annual mean precipitation arrangement over Catalonia.
Transition probability estimates for non-Markov multi-state models.
Titman, Andrew C
2015-12-01
Non-parametric estimation of the transition probabilities in multi-state models is considered for non-Markov processes. Firstly, a generalization of the estimator of Pepe et al., (1991) (Statistics in Medicine) is given for a class of progressive multi-state models based on the difference between Kaplan-Meier estimators. Secondly, a general estimator for progressive or non-progressive models is proposed based upon constructed univariate survival or competing risks processes which retain the Markov property. The properties of the estimators and their associated standard errors are investigated through simulation. The estimators are demonstrated on datasets relating to survival and recurrence in patients with colon cancer and prothrombin levels in liver cirrhosis patients.
[Medical insurance estimation of risks].
Dunér, H
1975-11-01
The purpose of insurance medicine is to make a prognostic estimate of medical risk-factors in persons who apply for life, health, or accident insurance. Established risk-groups with a calculated average mortality and morbidity form the basis for premium rates and insurance terms. In most cases the applicant is accepted for insurance after a self-assessment of his health. Only around one per cent of the applications are refused, but there are cases in which the premium is raised, temporarily or permanently. It is often a matter of rough estimate, since the knowlege of the long-term prognosis for many diseases is incomplete. The insurance companies' rules for estimate of risk are revised at intervals of three or four years. The estimate of risk as regards life insurance has been gradually liberalised, while the medical conditions for health insurance have become stricter owing to an increase in the claims rate.
Biau, David Jean; Latouche, Aurélien; Porcher, Raphaël
2007-09-01
The Kaplan-Meier estimator is the current method for estimating the probability of an event to occur with time in orthopaedics. However, the Kaplan-Meier estimator was designed to estimate the probability of an event that eventually will occur for all patients, ie, death, and this does not hold for other outcomes. For example, not all patients will experience hip arthroplasty loosening because some may die first, and some may have their implant removed to treat infection or recurrent hip dislocation. Such events that preclude the observation of the event of interest are called competing events. We suggest the Kaplan-Meier estimator is inappropriate in the presence of competing events and show that it overestimates the probability of the event of interest to occur with time. The cumulative incidence estimator is an alternative approach to Kaplan-Meier in situations where competing risks are likely. Three common situations include revision for implant loosening in the long-term followup of arthroplasties or implant failure in the context of limb-salvage surgery or femoral neck fracture.
Akanda, Md Abdus Salam; Alpizar-Jara, Russell
2014-01-01
Modeling individual heterogeneity in capture probabilities has been one of the most challenging tasks in capture–recapture studies. Heterogeneity in capture probabilities can be modeled as a function of individual covariates, but correlation structure among capture occasions should be taking into account. A proposed generalized estimating equations (GEE) and generalized linear mixed modeling (GLMM) approaches can be used to estimate capture probabilities and population size for capture–recapture closed population models. An example is used for an illustrative application and for comparison with currently used methodology. A simulation study is also conducted to show the performance of the estimation procedures. Our simulation results show that the proposed quasi-likelihood based on GEE approach provides lower SE than partial likelihood based on either generalized linear models (GLM) or GLMM approaches for estimating population size in a closed capture–recapture experiment. Estimator performance is good if a large proportion of individuals are captured. For cases where only a small proportion of individuals are captured, the estimates become unstable, but the GEE approach outperforms the other methods. PMID:24772290
Structural health monitoring and probability of detection estimation
NASA Astrophysics Data System (ADS)
Forsyth, David S.
2016-02-01
Structural health monitoring (SHM) methods are often based on nondestructive testing (NDT) sensors and are often proposed as replacements for NDT to lower cost and/or improve reliability. In order to take advantage of SHM for life cycle management, it is necessary to determine the Probability of Detection (POD) of the SHM system just as for traditional NDT to ensure that the required level of safety is maintained. Many different possibilities exist for SHM systems, but one of the attractive features of SHM versus NDT is the ability to take measurements very simply after the SHM system is installed. Using a simple statistical model of POD, some authors have proposed that very high rates of SHM system data sampling can result in high effective POD even in situations where an individual test has low POD. In this paper, we discuss the theoretical basis for determining the effect of repeated inspections, and examine data from SHM experiments against this framework to show how the effective POD from multiple tests can be estimated.
Semi-supervised dimensionality reduction using estimated class membership probabilities
NASA Astrophysics Data System (ADS)
Li, Wei; Ruan, Qiuqi; Wan, Jun
2012-10-01
In solving pattern-recognition tasks with partially labeled training data, the semi-supervised dimensionality reduction method, which considers both labeled and unlabeled data, is preferable for improving the classification and generalization capability of the testing data. Among such techniques, graph-based semi-supervised learning methods have attracted a lot of attention due to their appealing properties in discovering discriminative structure and geometric structure of data points. Although they have achieved remarkable success, they cannot promise good performance when the size of the labeled data set is small, as a result of inaccurate class matrix variance approximated by insufficient labeled training data. In this paper, we tackle this problem by combining class membership probabilities estimated from unlabeled data and ground-truth class information associated with labeled data to more precisely characterize the class distribution. Therefore, it is expected to enhance performance in classification tasks. We refer to this approach as probabilistic semi-supervised discriminant analysis (PSDA). The proposed PSDA is applied to face and facial expression recognition tasks and is evaluated using the ORL, Extended Yale B, and CMU PIE face databases and the Cohn-Kanade facial expression database. The promising experimental results demonstrate the effectiveness of our proposed method.
Conditional Probabilities for Large Events Estimated by Small Earthquake Rate
NASA Astrophysics Data System (ADS)
Wu, Yi-Hsuan; Chen, Chien-Chih; Li, Hsien-Chi
2016-01-01
We examined forecasting quiescence and activation models to obtain the conditional probability that a large earthquake will occur in a specific time period on different scales in Taiwan. The basic idea of the quiescence and activation models is to use earthquakes that have magnitudes larger than the completeness magnitude to compute the expected properties of large earthquakes. We calculated the probability time series for the whole Taiwan region and for three subareas of Taiwan—the western, eastern, and northeastern Taiwan regions—using 40 years of data from the Central Weather Bureau catalog. In the probability time series for the eastern and northeastern Taiwan regions, a high probability value is usually yielded in cluster events such as events with foreshocks and events that all occur in a short time period. In addition to the time series, we produced probability maps by calculating the conditional probability for every grid point at the time just before a large earthquake. The probability maps show that high probability values are yielded around the epicenter before a large earthquake. The receiver operating characteristic (ROC) curves of the probability maps demonstrate that the probability maps are not random forecasts, but also suggest that lowering the magnitude of a forecasted large earthquake may not improve the forecast method itself. From both the probability time series and probability maps, it can be observed that the probability obtained from the quiescence model increases before a large earthquake and the probability obtained from the activation model increases as the large earthquakes occur. The results lead us to conclude that the quiescence model has better forecast potential than the activation model.
Estimating Terrorist Risk with Possibility Theory
J.L. Darby
2004-11-30
This report summarizes techniques that use possibility theory to estimate the risk of terrorist acts. These techniques were developed under the sponsorship of the Department of Homeland Security (DHS) as part of the National Infrastructure Simulation Analysis Center (NISAC) project. The techniques have been used to estimate the risk of various terrorist scenarios to support NISAC analyses during 2004. The techniques are based on the Logic Evolved Decision (LED) methodology developed over the past few years by Terry Bott and Steve Eisenhawer at LANL. [LED] The LED methodology involves the use of fuzzy sets, possibility theory, and approximate reasoning. LED captures the uncertainty due to vagueness and imprecision that is inherent in the fidelity of the information available for terrorist acts; probability theory cannot capture these uncertainties. This report does not address the philosophy supporting the development of nonprobabilistic approaches, and it does not discuss possibility theory in detail. The references provide a detailed discussion of these subjects. [Shafer] [Klir and Yuan] [Dubois and Prade] Suffice to say that these approaches were developed to address types of uncertainty that cannot be addressed by a probability measure. An earlier report discussed in detail the problems with using a probability measure to evaluate terrorist risk. [Darby Methodology]. Two related techniques are discussed in this report: (1) a numerical technique, and (2) a linguistic technique. The numerical technique uses traditional possibility theory applied to crisp sets, while the linguistic technique applies possibility theory to fuzzy sets. Both of these techniques as applied to terrorist risk for NISAC applications are implemented in software called PossibleRisk. The techniques implemented in PossibleRisk were developed specifically for use in estimating terrorist risk for the NISAC program. The LEDTools code can be used to perform the same linguistic evaluation as
Exaggerated risk: prospect theory and probability weighting in risky choice.
Kusev, Petko; van Schaik, Paul; Ayton, Peter; Dent, John; Chater, Nick
2009-11-01
In 5 experiments, we studied precautionary decisions in which participants decided whether or not to buy insurance with specified cost against an undesirable event with specified probability and cost. We compared the risks taken for precautionary decisions with those taken for equivalent monetary gambles. Fitting these data to Tversky and Kahneman's (1992) prospect theory, we found that the weighting function required to model precautionary decisions differed from that required for monetary gambles. This result indicates a failure of the descriptive invariance axiom of expected utility theory. For precautionary decisions, people overweighted small, medium-sized, and moderately large probabilities-they exaggerated risks. This effect is not anticipated by prospect theory or experience-based decision research (Hertwig, Barron, Weber, & Erev, 2004). We found evidence that exaggerated risk is caused by the accessibility of events in memory: The weighting function varies as a function of the accessibility of events. This suggests that people's experiences of events leak into decisions even when risk information is explicitly provided. Our findings highlight a need to investigate how variation in decision content produces variation in preferences for risk.
Assessing Risks through the Determination of Rare Event Probabilities.
1980-07-01
independent consultants as to the risk posed by proposed LNG Tanker movement in the New York harbor. Table 1 (taken from Fairley (1977)) represents a summary of...Consistency Analysis for LNG Tanker Movements In a critique of the study concerning the safety of LNG tanker movements, Fairley (1977) notes that the...probabilities of most factors could possibly be upwardly corrected. The upward correc- tions are summarized in the following table taken from Fairley (1974, p
Chen, Xinguang; Lin, Feng
2013-01-01
Background and objective New analytical tools are needed to advance tobacco research, tobacco control planning and tobacco use prevention practice. In this study, we validated a method to extract information from cross-sectional survey for quantifying population dynamics of adolescent smoking behavior progression. Methods With a 3-stage 7-path model, probabilities of smoking behavior progression were estimated employing the Probabilistic Discrete Event System (PDES) method and the cross-sectional data from 1997-2006 National Survey on Drug Use and Health (NSDUH). Validity of the PDES method was assessed using data from the National Longitudinal Survey of Youth 1997 and trends in smoking transition covering the period during which funding for tobacco control was cut substantively in 2003 in the United States. Results Probabilities for all seven smoking progression paths were successfully estimated with the PDES method and the NSDUH data. The absolute difference in the estimated probabilities between the two approaches varied from 0.002 to 0.076 (p>0.05 for all) and were highly correlated with each other (R2=0.998, p<0.01). Changes in the estimated transitional probabilities across the 1997-2006 reflected the 2003 funding cut for tobacco control. Conclusions The PDES method has validity in quantifying population dynamics of smoking behavior progression with cross-sectional survey data. The estimated transitional probabilities add new evidence supporting more advanced tobacco research, tobacco control planning and tobacco use prevention practice. This method can be easily extended to study other health risk behaviors. PMID:25279247
Estimating earthquake-induced failure probability and downtime of critical facilities.
Porter, Keith; Ramer, Kyle
2012-01-01
Fault trees have long been used to estimate failure risk in earthquakes, especially for nuclear power plants (NPPs). One interesting application is that one can assess and manage the probability that two facilities - a primary and backup - would be simultaneously rendered inoperative in a single earthquake. Another is that one can calculate the probabilistic time required to restore a facility to functionality, and the probability that, during any given planning period, the facility would be rendered inoperative for any specified duration. A large new peer-reviewed library of component damageability and repair-time data for the first time enables fault trees to be used to calculate the seismic risk of operational failure and downtime for a wide variety of buildings other than NPPs. With the new library, seismic risk of both the failure probability and probabilistic downtime can be assessed and managed, considering the facility's unique combination of structural and non-structural components, their seismic installation conditions, and the other systems on which the facility relies. An example is offered of real computer data centres operated by a California utility. The fault trees were created and tested in collaboration with utility operators, and the failure probability and downtime results validated in several ways.
Estimating risks of perinatal death.
Smith, Gordon C S
2005-01-01
The relative and absolute risks of perinatal death that are estimated from observational studies are used frequently in counseling about obstetric intervention. The statistical basis for these estimates therefore is crucial, but many studies are seriously flawed. In this review, a number of aspects of the approach to the estimation of the risk of perinatal death are addressed. Key factors in the analysis include (1) the definition of the cause of the death, (2) differentiation between antepartum and intrapartum events, (3) the use of the appropriate denominator for the given cause of death, (4) the assessment of the cumulative risk where appropriate, (5) the use of appropriate statistical tests, (6) the stratification of analysis of delivery-related deaths by gestational age, and (7) the specific features of multiple pregnancy, which include the correct determination of the timing of antepartum stillbirth and the use of paired statistical tests when outcomes are compared in relation to the birth order of twin pairs.
The effect of framing actuarial risk probabilities on involuntary civil commitment decisions.
Scurich, Nicholas; John, Richard S
2011-04-01
Despite a proliferation of actuarial risk assessment instruments, empirical research on the communication of violence risk is scant and there is virtually no research on the consumption of actuarial risk assessment. Using a 2 × 3 Latin Square factorial design, this experiment tested whether decision-makers are sensitive to varying levels of risk expressed probabilistically and whether the framing of actuarial risk probabilities is consequential for commitment decisions. Consistent with research on attribute framing, in which describing an attribute in terms of its complement leads to different conclusions, this experiment found that the way actuarial risk estimates are framed leads to disparate commitment decisions. For example, risk framed as 26% probability of violence generally led decision-makers to authorize commitment, whereas the same risk framed in the complement, a 74% probability of no violence, generally led decision-makers to release. This result was most pronounced for moderate risk levels. Implications for the risk communication format debate, forensic practice and research are discussed.
NASA Astrophysics Data System (ADS)
Wang, Q. J.
1990-12-01
Unbiased estimators of probability weighted moments (PWM) and partial probability weighted moments (PPWM) from systematic and historical flood information are derived. Applications are made to estimating parameters and quantiles of the generalized extreme value (GEV) distribution. The effect of lower bound censoring, which might be deliberately introduced in practice, is also considered.
NASA Astrophysics Data System (ADS)
Baer, P.; Mastrandrea, M.
2006-12-01
Simple probabilistic models which attempt to estimate likely transient temperature change from specified CO2 emissions scenarios must make assumptions about at least six uncertain aspects of the causal chain between emissions and temperature: current radiative forcing (including but not limited to aerosols), current land use emissions, carbon sinks, future non-CO2 forcing, ocean heat uptake, and climate sensitivity. Of these, multiple PDFs (probability density functions) have been published for the climate sensitivity, a couple for current forcing and ocean heat uptake, one for future non-CO2 forcing, and none for current land use emissions or carbon cycle uncertainty (which are interdependent). Different assumptions about these parameters, as well as different model structures, will lead to different estimates of likely temperature increase from the same emissions pathway. Thus policymakers will be faced with a range of temperature probability distributions for the same emissions scenarios, each described by a central tendency and spread. Because our conventional understanding of uncertainty and probability requires that a probabilistically defined variable of interest have only a single mean (or median, or modal) value and a well-defined spread, this "multidimensional" uncertainty defies straightforward utilization in policymaking. We suggest that there are no simple solutions to the questions raised. Crucially, we must dispel the notion that there is a "true" probability probabilities of this type are necessarily subjective, and reasonable people may disagree. Indeed, we suggest that what is at stake is precisely the question, what is it reasonable to believe, and to act as if we believe? As a preliminary suggestion, we demonstrate how the output of a simple probabilistic climate model might be evaluated regarding the reasonableness of the outputs it calculates with different input PDFs. We suggest further that where there is insufficient evidence to clearly
NASA Technical Reports Server (NTRS)
Havens, K. A.; Minster, T. C.; Thadani, S. G.
1976-01-01
The probability of error or, alternatively, the probability of correct classification (PCC) is an important criterion in analyzing the performance of a classifier. Labeled samples (those with ground truth) are usually employed to evaluate the performance of a classifier. Occasionally, the numbers of labeled samples are inadequate, or no labeled samples are available to evaluate a classifier's performance; for example, when crop signatures from one area from which ground truth is available are used to classify another area from which no ground truth is available. This paper reports the results of an experiment to estimate the probability of error using unlabeled test samples (i.e., without the aid of ground truth).
Compositional cokriging for mapping the probability risk of groundwater contamination by nitrates.
Pardo-Igúzquiza, Eulogio; Chica-Olmo, Mario; Luque-Espinar, Juan A; Rodríguez-Galiano, Víctor
2015-11-01
Contamination by nitrates is an important cause of groundwater pollution and represents a potential risk to human health. Management decisions must be made using probability maps that assess the nitrate concentration potential of exceeding regulatory thresholds. However these maps are obtained with only a small number of sparse monitoring locations where the nitrate concentrations have been measured. It is therefore of great interest to have an efficient methodology for obtaining those probability maps. In this paper, we make use of the fact that the discrete probability density function is a compositional variable. The spatial discrete probability density function is estimated by compositional cokriging. There are several advantages in using this approach: (i) problems of classical indicator cokriging, like estimates outside the interval (0,1) and order relations, are avoided; (ii) secondary variables (e.g. aquifer parameters) can be included in the estimation of the probability maps; (iii) uncertainty maps of the probability maps can be obtained; (iv) finally there are modelling advantages because the variograms and cross-variograms of real variables that do not have the restrictions of indicator variograms and indicator cross-variograms. The methodology was applied to the Vega de Granada aquifer in Southern Spain and the advantages of the compositional cokriging approach were demonstrated.
NASA Astrophysics Data System (ADS)
Fung, D. C. N.; Wang, J. P.; Chang, S. H.; Chang, S. C.
2014-12-01
Using a revised statistical model built on past seismic probability models, the probability of different magnitude earthquakes occurring within variable timespans can be estimated. The revised model is based on Poisson distribution and includes the use of best-estimate values of the probability distribution of different magnitude earthquakes recurring from a fault from literature sources. Our study aims to apply this model to the Taipei metropolitan area with a population of 7 million, which lies in the Taipei Basin and is bounded by two normal faults: the Sanchaio and Taipei faults. The Sanchaio fault is suggested to be responsible for previous large magnitude earthquakes, such as the 1694 magnitude 7 earthquake in northwestern Taipei (Cheng et. al., 2010). Based on a magnitude 7 earthquake return period of 543 years, the model predicts the occurrence of a magnitude 7 earthquake within 20 years at 1.81%, within 79 years at 6.77% and within 300 years at 21.22%. These estimates increase significantly when considering a magnitude 6 earthquake; the chance of one occurring within the next 20 years is estimated to be 3.61%, 79 years at 13.54% and 300 years at 42.45%. The 79 year period represents the average lifespan of the Taiwan population. In contrast, based on data from 2013, the probability of Taiwan residents experiencing heart disease or malignant neoplasm is 11.5% and 29%. The inference of this study is that the calculated risk that the Taipei population is at from a potentially damaging magnitude 6 or greater earthquake occurring within their lifetime is just as great as of suffering from a heart attack or other health ailments.
A new parametric method of estimating the joint probability density
NASA Astrophysics Data System (ADS)
Alghalith, Moawia
2017-04-01
We present simple parametric methods that overcome major limitations of the literature on joint/marginal density estimation. In doing so, we do not assume any form of marginal or joint distribution. Furthermore, using our method, a multivariate density can be easily estimated if we know only one of the marginal densities. We apply our methods to financial data.
Almost efficient estimation of relative risk regression
Fitzmaurice, Garrett M.; Lipsitz, Stuart R.; Arriaga, Alex; Sinha, Debajyoti; Greenberg, Caprice; Gawande, Atul A.
2014-01-01
Relative risks (RRs) are often considered the preferred measures of association in prospective studies, especially when the binary outcome of interest is common. In particular, many researchers regard RRs to be more intuitively interpretable than odds ratios. Although RR regression is a special case of generalized linear models, specifically with a log link function for the binomial (or Bernoulli) outcome, the resulting log-binomial regression does not respect the natural parameter constraints. Because log-binomial regression does not ensure that predicted probabilities are mapped to the [0,1] range, maximum likelihood (ML) estimation is often subject to numerical instability that leads to convergence problems. To circumvent these problems, a number of alternative approaches for estimating RR regression parameters have been proposed. One approach that has been widely studied is the use of Poisson regression estimating equations. The estimating equations for Poisson regression yield consistent, albeit inefficient, estimators of the RR regression parameters. We consider the relative efficiency of the Poisson regression estimator and develop an alternative, almost efficient estimator for the RR regression parameters. The proposed method uses near-optimal weights based on a Maclaurin series (Taylor series expanded around zero) approximation to the true Bernoulli or binomial weight function. This yields an almost efficient estimator while avoiding convergence problems. We examine the asymptotic relative efficiency of the proposed estimator for an increase in the number of terms in the series. Using simulations, we demonstrate the potential for convergence problems with standard ML estimation of the log-binomial regression model and illustrate how this is overcome using the proposed estimator. We apply the proposed estimator to a study of predictors of pre-operative use of beta blockers among patients undergoing colorectal surgery after diagnosis of colon cancer. PMID
A CONDITIONAL PROBABILITY APPROACH FOR ANALYZING SURVEY DATA TO ESTIMATE PROBABILITY OF IMPAIRMENT
A question that arises is how can survey data, collected with a random design, provide an initial screening for identifying unsampled areas that are likely to have biological impairment? A random sampling design provides estimates of relative fraction of the population of interes...
Betrie, Getnet D; Sadiq, Rehan; Nichol, Craig; Morin, Kevin A; Tesfamariam, Solomon
2016-01-15
Acid rock drainage (ARD) is a major environmental problem that poses significant environmental risks during and after mining activities. A new methodology for environmental risk assessment based on probability bounds and a geochemical speciation model (PHREEQC) is presented. The methodology provides conservative and non-conservative ways of estimating risk of heavy metals posed to selected endpoints probabilistically, while propagating data and parameter uncertainties throughout the risk assessment steps. The methodology is demonstrated at a minesite located in British Columbia, Canada. The result of the methodology for the case study minesite shows the fate-and-transport of heavy metals is well simulated in the mine environment. In addition, the results of risk characterization for the case study show that there is risk due to transport of heavy metals into the environment.
Estimating the Probability of Electrical Short Circuits from Tin Whiskers. Part 2
NASA Technical Reports Server (NTRS)
Courey, Karim J.; Asfour, Shihab S.; Onar, Arzu; Bayliss, Jon A.; Ludwig, Larry L.; Wright, Maria C.
2010-01-01
To comply with lead-free legislation, many manufacturers have converted from tin-lead to pure tin finishes of electronic components. However, pure tin finishes have a greater propensity to grow tin whiskers than tin-lead finishes. Since tin whiskers present an electrical short circuit hazard in electronic components, simulations have been developed to quantify the risk of said short circuits occurring. Existing risk simulations make the assumption that when a free tin whisker has bridged two adjacent exposed electrical conductors, the result is an electrical short circuit. This conservative assumption is made because shorting is a random event that had an unknown probability associated with it. Note however that due to contact resistance electrical shorts may not occur at lower voltage levels. In our first article we developed an empirical probability model for tin whisker shorting. In this paper, we develop a more comprehensive empirical model using a refined experiment with a larger sample size, in which we studied the effect of varying voltage on the breakdown of the contact resistance which leads to a short circuit. From the resulting data we estimated the probability distribution of an electrical short, as a function of voltage. In addition, the unexpected polycrystalline structure seen in the focused ion beam (FIB) cross section in the first experiment was confirmed in this experiment using transmission electron microscopy (TEM). The FIB was also used to cross section two card guides to facilitate the measurement of the grain size of each card guide's tin plating to determine its finish .
Estimating the Probability of Electrical Short Circuits from Tin Whiskers. Part 2
NASA Technical Reports Server (NTRS)
Courey, Karim J.; Asfour, Shihab S.; Onar, Arzu; Bayliss, Jon A.; Ludwig, Larry L.; Wright, Maria C.
2009-01-01
To comply with lead-free legislation, many manufacturers have converted from tin-lead to pure tin finishes of electronic components. However, pure tin finishes have a greater propensity to grow tin whiskers than tin-lead finishes. Since tin whiskers present an electrical short circuit hazard in electronic components, simulations have been developed to quantify the risk of said short circuits occurring. Existing risk simulations make the assumption that when a free tin whisker has bridged two adjacent exposed electrical conductors, the result is an electrical short circuit. This conservative assumption is made because shorting is a random event that had an unknown probability associated with it. Note however that due to contact resistance electrical shorts may not occur at lower voltage levels. In our first article we developed an empirical probability model for tin whisker shorting. In this paper, we develop a more comprehensive empirical model using a refined experiment with a larger sample size, in which we studied the effect of varying voltage on the breakdown of the contact resistance which leads to a short circuit. From the resulting data we estimated the probability distribution of an electrical short, as a function of voltage.
Probability Distribution Extraction from TEC Estimates based on Kernel Density Estimation
NASA Astrophysics Data System (ADS)
Demir, Uygar; Toker, Cenk; Çenet, Duygu
2016-07-01
Statistical analysis of the ionosphere, specifically the Total Electron Content (TEC), may reveal important information about its temporal and spatial characteristics. One of the core metrics that express the statistical properties of a stochastic process is its Probability Density Function (pdf). Furthermore, statistical parameters such as mean, variance and kurtosis, which can be derived from the pdf, may provide information about the spatial uniformity or clustering of the electron content. For example, the variance differentiates between a quiet ionosphere and a disturbed one, whereas kurtosis differentiates between a geomagnetic storm and an earthquake. Therefore, valuable information about the state of the ionosphere (and the natural phenomena that cause the disturbance) can be obtained by looking at the statistical parameters. In the literature, there are publications which try to fit the histogram of TEC estimates to some well-known pdf.s such as Gaussian, Exponential, etc. However, constraining a histogram to fit to a function with a fixed shape will increase estimation error, and all the information extracted from such pdf will continue to contain this error. In such techniques, it is highly likely to observe some artificial characteristics in the estimated pdf which is not present in the original data. In the present study, we use the Kernel Density Estimation (KDE) technique to estimate the pdf of the TEC. KDE is a non-parametric approach which does not impose a specific form on the TEC. As a result, better pdf estimates that almost perfectly fit to the observed TEC values can be obtained as compared to the techniques mentioned above. KDE is particularly good at representing the tail probabilities, and outliers. We also calculate the mean, variance and kurtosis of the measured TEC values. The technique is applied to the ionosphere over Turkey where the TEC values are estimated from the GNSS measurement from the TNPGN-Active (Turkish National Permanent
A Non-Parametric Probability Density Estimator and Some Applications.
1984-05-01
but she always made them easier. My children, Alison and Adam, did not always make °’ things easier but did keep my efforts in perspective. I love...Since one goal of this research is to develop a " handi - off" estimator, these choices will either be made a priori 24
Estimation of probability of failure for damage-tolerant aerospace structures
NASA Astrophysics Data System (ADS)
Halbert, Keith
The majority of aircraft structures are designed to be damage-tolerant such that safe operation can continue in the presence of minor damage. It is necessary to schedule inspections so that minor damage can be found and repaired. It is generally not possible to perform structural inspections prior to every flight. The scheduling is traditionally accomplished through a deterministic set of methods referred to as Damage Tolerance Analysis (DTA). DTA has proven to produce safe aircraft but does not provide estimates of the probability of failure of future flights or the probability of repair of future inspections. Without these estimates maintenance costs cannot be accurately predicted. Also, estimation of failure probabilities is now a regulatory requirement for some aircraft. The set of methods concerned with the probabilistic formulation of this problem are collectively referred to as Probabilistic Damage Tolerance Analysis (PDTA). The goal of PDTA is to control the failure probability while holding maintenance costs to a reasonable level. This work focuses specifically on PDTA for fatigue cracking of metallic aircraft structures. The growth of a crack (or cracks) must be modeled using all available data and engineering knowledge. The length of a crack can be assessed only indirectly through evidence such as non-destructive inspection results, failures or lack of failures, and the observed severity of usage of the structure. The current set of industry PDTA tools are lacking in several ways: they may in some cases yield poor estimates of failure probabilities, they cannot realistically represent the variety of possible failure and maintenance scenarios, and they do not allow for model updates which incorporate observed evidence. A PDTA modeling methodology must be flexible enough to estimate accurately the failure and repair probabilities under a variety of maintenance scenarios, and be capable of incorporating observed evidence as it becomes available. This
Estimation of post-test probabilities by residents: Bayesian reasoning versus heuristics?
Hall, Stacey; Phang, Sen Han; Schaefer, Jeffrey P; Ghali, William; Wright, Bruce; McLaughlin, Kevin
2014-08-01
Although the process of diagnosing invariably begins with a heuristic, we encourage our learners to support their diagnoses by analytical cognitive processes, such as Bayesian reasoning, in an attempt to mitigate the effects of heuristics on diagnosing. There are, however, limited data on the use ± impact of Bayesian reasoning on the accuracy of disease probability estimates. In this study our objective was to explore whether Internal Medicine residents use a Bayesian process to estimate disease probabilities by comparing their disease probability estimates to literature-derived Bayesian post-test probabilities. We gave 35 Internal Medicine residents four clinical vignettes in the form of a referral letter and asked them to estimate the post-test probability of the target condition in each case. We then compared these to literature-derived probabilities. For each vignette the estimated probability was significantly different from the literature-derived probability. For the two cases with low literature-derived probability our participants significantly overestimated the probability of these target conditions being the correct diagnosis, whereas for the two cases with high literature-derived probability the estimated probability was significantly lower than the calculated value. Our results suggest that residents generate inaccurate post-test probability estimates. Possible explanations for this include ineffective application of Bayesian reasoning, attribute substitution whereby a complex cognitive task is replaced by an easier one (e.g., a heuristic), or systematic rater bias, such as central tendency bias. Further studies are needed to identify the reasons for inaccuracy of disease probability estimates and to explore ways of improving accuracy.
Estimating background and threshold nitrate concentrations using probability graphs
Panno, S.V.; Kelly, W.R.; Martinsek, A.T.; Hackley, Keith C.
2006-01-01
Because of the ubiquitous nature of anthropogenic nitrate (NO 3-) in many parts of the world, determining background concentrations of NO3- in shallow ground water from natural sources is probably impossible in most environments. Present-day background must now include diffuse sources of NO3- such as disruption of soils and oxidation of organic matter, and atmospheric inputs from products of combustion and evaporation of ammonia from fertilizer and livestock waste. Anomalies can be defined as NO3- derived from nitrogen (N) inputs to the environment from anthropogenic activities, including synthetic fertilizers, livestock waste, and septic effluent. Cumulative probability graphs were used to identify threshold concentrations separating background and anomalous NO3-N concentrations and to assist in the determination of sources of N contamination for 232 spring water samples and 200 well water samples from karst aquifers. Thresholds were 0.4, 2.5, and 6.7 mg/L for spring water samples, and 0.1, 2.1, and 17 mg/L for well water samples. The 0.4 and 0.1 mg/L values are assumed to represent thresholds for present-day precipitation. Thresholds at 2.5 and 2.1 mg/L are interpreted to represent present-day background concentrations of NO3-N. The population of spring water samples with concentrations between 2.5 and 6.7 mg/L represents an amalgam of all sources of NO3- in the ground water basins that feed each spring; concentrations >6.7 mg/L were typically samples collected soon after springtime application of synthetic fertilizer. The 17 mg/L threshold (adjusted to 15 mg/L) for well water samples is interpreted as the level above which livestock wastes dominate the N sources. Copyright ?? 2006 The Author(s).
Effect of Prior Probability Quality on Biased Time-Delay Estimation
Byram, Brett C.; Trahey, Gregg E.; Palmeri, Mark L.
2012-01-01
When properly constructed, biased estimators are known to produce lower mean-square errors than unbiased estimators. A biased estimator for the problem of ultrasound time-delay estimation was recently proposed. The proposed estimator incorporates knowledge of adjacent displacement estimates into the final estimate of a displacement. This is accomplished by using adjacent estimates to create a prior probability on the current estimate. Theory and simulations are used to investigate how the prior probability impacts the final estimate. The results show that with estimation quality on the order of the Cramer-Rao lower bound at adjacent locations, the local estimate in question should generally exceed the Cramer-Rao lower-bound limitations on performance of an unbiased estimator. The results as a whole provide additional confidence for the proposed estimator. PMID:22724313
The Estimation of Probability of Extreme Events for Small Samples
NASA Astrophysics Data System (ADS)
Pisarenko, V. F.; Rodkin, M. V.
2017-02-01
The most general approach to the study of rare extreme events is based on the extreme value theory. The fundamental General Extreme Value Distribution lies in the basis of this theory serving as the limit distribution for normalized maxima. It depends on three parameters. Usually the method of maximum likelihood (ML) is used for the estimation that possesses well-known optimal asymptotic properties. However, this method works efficiently only when sample size is large enough ( 200-500), whereas in many applications the sample size does not exceed 50-100. For such sizes, the advantage of the ML method in efficiency is not guaranteed. We have found that for this situation the method of statistical moments (SM) works more efficiently over other methods. The details of the estimation for small samples are studied. The SM is applied to the study of extreme earthquakes in three large virtual seismic zones, representing the regime of seismicity in subduction zones, intracontinental regime of seismicity, and the regime in mid-ocean ridge zones. The 68%-confidence domains for pairs of parameter (ξ, σ) and (σ, μ) are derived.
Estimation of the size of a closed population when capture probabilities vary among animals
Burnham, K.P.; Overton, W.S.
1978-01-01
A model which allows capture probabilities to vary by individuals is introduced for multiple recapture studies n closed populations. The set of individual capture probabilities is modelled as a random sample from an arbitrary probability distribution over the unit interval. We show that the capture frequencies are a sufficient statistic. A nonparametric estimator of population size is developed based on the generalized jackknife; this estimator is found to be a linear combination of the capture frequencies. Finally, tests of underlying assumptions are presented.
Estimating the Probability of a Diffusing Target Encountering a Stationary Sensor.
1985-07-01
7 RD-R1577 6- 44 ESTIMATING THE PROBABILITY OF A DIFFUSING TARGET i/i ENCOUNTERING R STATIONARY SENSOR(U) NAVAL POSTGRADUATE U SCHOOL MONTEREY CA...8217,: *.:.; - -*.. ,’.-,:;;’.’.. ’,. ,. .*.’.- 4 6 6- ..- .-,,.. : .-.;.- -. NPS55-85-013 NAVAL POSTGRADUATE SCHOOL Monterey, California ESTIMATING THE PROBABILITY OF A DIFFUSING TARGET...PROBABILITY OF A DIFFUSING Technical TARGET ENCOUNTERING A STATIONARY SENSOR S. PERFORMING ORG. REPORT NUMBER 7. AUTHOR(@) S. CONTRACT OR GRANT NUMBER(a
Some considerations on the definition of risk based on concepts of systems theory and probability.
Andretta, Massimo
2014-07-01
The concept of risk has been applied in many modern science and technology fields. Despite its successes in many applicative fields, there is still not a well-established vision and universally accepted definition of the principles and fundamental concepts of the risk assessment discipline. As emphasized recently, the risk fields suffer from a lack of clarity on their scientific bases that can define, in a unique theoretical framework, the general concepts in the different areas of application. The aim of this article is to make suggestions for another perspective of risk definition that could be applied and, in a certain sense, generalize some of the previously known definitions (at least in the fields of technical and scientific applications). By drawing on my experience of risk assessment in different applicative situations (particularly in the risk estimation for major industrial accidents, and in the health and ecological risk assessment for contaminated sites), I would like to revise some general and foundational concepts of risk analysis in as consistent a manner as possible from the axiomatic/deductive point of view. My proposal is based on the fundamental concepts of the systems theory and of the probability. In this way, I try to frame, in a single, broad, and general theoretical context some fundamental concepts and principles applicable in many different fields of risk assessment. I hope that this article will contribute to the revitalization and stimulation of useful discussions and new insights into the key issues and theoretical foundations of risk assessment disciplines.
Overfitting, generalization, and MSE in class probability estimation with high-dimensional data.
Kim, Kyung In; Simon, Richard
2014-03-01
Accurate class probability estimation is important for medical decision making but is challenging, particularly when the number of candidate features exceeds the number of cases. Special methods have been developed for nonprobabilistic classification, but relatively little attention has been given to class probability estimation with numerous candidate variables. In this paper, we investigate overfitting in the development of regularized class probability estimators. We investigate the relation between overfitting and accurate class probability estimation in terms of mean square error. Using simulation studies based on real datasets, we found that some degree of overfitting can be desirable for reducing mean square error. We also introduce a mean square error decomposition for class probability estimation that helps clarify the relationship between overfitting and prediction accuracy.
Assessment of Methods for Estimating Risk to Birds from ...
The U.S. EPA Ecological Risk Assessment Support Center (ERASC) announced the release of the final report entitled, Assessment of Methods for Estimating Risk to Birds from Ingestion of Contaminated Grit Particles. This report evaluates approaches for estimating the probability of ingestion by birds of contaminated particles such as pesticide granules or lead particles (i.e. shot or bullet fragments). In addition, it presents an approach for using this information to estimate the risk of mortality to birds from ingestion of lead particles. Response to ERASC Request #16
Bayesian estimation of the probability of asbestos exposure from lung fiber counts.
Weichenthal, Scott; Joseph, Lawrence; Bélisle, Patrick; Dufresne, André
2010-06-01
Asbestos exposure is a well-known risk factor for various lung diseases, and when they occur, workmen's compensation boards need to make decisions concerning the probability the cause is work related. In the absence of a definitive work history, measures of short and long asbestos fibers as well as counts of asbestos bodies in the lung can be used as diagnostic tests for asbestos exposure. Typically, data from one or more lung samples are available to estimate the probability of asbestos exposure, often by comparing the values with those from a reference nonexposed population. As there is no gold standard measure, we explore a variety of latent class models that take into account the mixed discrete/continuous nature of the data, that each subject may provide data from more than one lung sample, and that the within-subject results across different samples may be correlated. Our methods can be useful to compensation boards in providing individual level probabilities of exposure based on available data, to researchers who are studying the test properties for the various measures used in this area, and more generally, to other test situations with similar data structure.
On the estimation of risk associated with an attenuation prediction
NASA Technical Reports Server (NTRS)
Crane, R. K.
1992-01-01
Viewgraphs from a presentation on the estimation of risk associated with an attenuation prediction is presented. Topics covered include: link failure - attenuation exceeding a specified threshold for a specified time interval or intervals; risk - the probability of one or more failures during the lifetime of the link or during a specified accounting interval; the problem - modeling the probability of attenuation by rainfall to provide a prediction of the attenuation threshold for a specified risk; and an accounting for the inadequacy of a model or models.
The development of posterior probability models in risk-based integrity modeling.
Thodi, Premkumar N; Khan, Faisal I; Haddara, Mahmoud R
2010-03-01
There is a need for accurate modeling of mechanisms causing material degradation of equipment in process installation, to ensure safety and reliability of the equipment. Degradation mechanisms are stochastic processes. They can be best described using risk-based approaches. Risk-based integrity assessment quantifies the level of risk to which the individual components are subjected and provides means to mitigate them in a safe and cost-effective manner. The uncertainty and variability in structural degradations can be best modeled by probability distributions. Prior probability models provide initial description of the degradation mechanisms. As more inspection data become available, these prior probability models can be revised to obtain posterior probability models, which represent the current system and can be used to predict future failures. In this article, a rejection sampling-based Metropolis-Hastings (M-H) algorithm is used to develop posterior distributions. The M-H algorithm is a Markov chain Monte Carlo algorithm used to generate a sequence of posterior samples without actually knowing the normalizing constant. Ignoring the transient samples in the generated Markov chain, the steady state samples are rejected or accepted based on an acceptance criterion. To validate the estimated parameters of posterior models, analytical Laplace approximation method is used to compute the integrals involved in the posterior function. Results of the M-H algorithm and Laplace approximations are compared with conjugate pair estimations of known prior and likelihood combinations. The M-H algorithm provides better results and hence it is used for posterior development of the selected priors for corrosion and cracking.
2014-01-01
Background Data on HCV-related cirrhosis progression are scarce in developing countries in general, and in Egypt in particular. The objective of this study was to estimate the probability of death and transition between different health stages of HCV (compensated cirrhosis, decompensated cirrhosis and hepatocellular carcinoma) for an Egyptian population of patients with HCV-related cirrhosis. Methods We used the “elicitation of expert opinions” method to obtain collective knowledge from a panel of 23 Egyptian experts (among whom 17 were hepatologists or gastroenterologists and 2 were infectiologists). The questionnaire was based on virtual medical cases and asked the experts to assess probability of death or probability of various cirrhosis complications. The design was a Delphi study: we attempted to obtain a consensus between experts via a series of questionnaires interspersed with group response feedback. Results We found substantial disparity between experts’ answers, and no consensus was reached at the end of the process. Moreover, we obtained high death probability and high risk of hepatocellular carcinoma. The annual transition probability to death was estimated at between 10.1% and 61.5% and the annual probability of occurrence of hepatocellular carcinoma was estimated at between 16.8% and 58.9% (depending on age, gender, time spent in cirrhosis and cirrhosis severity). Conclusions Our results show that eliciting expert opinions is not suited for determining the natural history of diseases due to practitioners’ difficulties in evaluating quantities. Cognitive bias occurring during this type of study might explain our results. PMID:24635942
Walsh, Michael G; Haseeb, M A
2014-01-01
Toxocariasis is increasingly recognized as an important neglected infection of poverty (NIP) in developed countries, and may constitute the most important NIP in the United States (US) given its association with chronic sequelae such as asthma and poor cognitive development. Its potential public health burden notwithstanding, toxocariasis surveillance is minimal throughout the US and so the true burden of disease remains uncertain in many areas. The Third National Health and Nutrition Examination Survey conducted a representative serologic survey of toxocariasis to estimate the prevalence of infection in diverse US subpopulations across different regions of the country. Using the NHANES III surveillance data, the current study applied the predicted probabilities of toxocariasis to the sociodemographic composition of New York census tracts to estimate the local probability of infection across the city. The predicted probability of toxocariasis ranged from 6% among US-born Latino women with a university education to 57% among immigrant men with less than a high school education. The predicted probability of toxocariasis exhibited marked spatial variation across the city, with particularly high infection probabilities in large sections of Queens, and smaller, more concentrated areas of Brooklyn and northern Manhattan. This investigation is the first attempt at small-area estimation of the probability surface of toxocariasis in a major US city. While this study does not define toxocariasis risk directly, it does provide a much needed tool to aid the development of toxocariasis surveillance in New York City.
Kruppa, Jochen; Liu, Yufeng; Biau, Gérard; Kohler, Michael; König, Inke R; Malley, James D; Ziegler, Andreas
2014-07-01
Probability estimation for binary and multicategory outcome using logistic and multinomial logistic regression has a long-standing tradition in biostatistics. However, biases may occur if the model is misspecified. In contrast, outcome probabilities for individuals can be estimated consistently with machine learning approaches, including k-nearest neighbors (k-NN), bagged nearest neighbors (b-NN), random forests (RF), and support vector machines (SVM). Because machine learning methods are rarely used by applied biostatisticians, the primary goal of this paper is to explain the concept of probability estimation with these methods and to summarize recent theoretical findings. Probability estimation in k-NN, b-NN, and RF can be embedded into the class of nonparametric regression learning machines; therefore, we start with the construction of nonparametric regression estimates and review results on consistency and rates of convergence. In SVMs, outcome probabilities for individuals are estimated consistently by repeatedly solving classification problems. For SVMs we review classification problem and then dichotomous probability estimation. Next we extend the algorithms for estimating probabilities using k-NN, b-NN, and RF to multicategory outcomes and discuss approaches for the multicategory probability estimation problem using SVM. In simulation studies for dichotomous and multicategory dependent variables we demonstrate the general validity of the machine learning methods and compare it with logistic regression. However, each method fails in at least one simulation scenario. We conclude with a discussion of the failures and give recommendations for selecting and tuning the methods. Applications to real data and example code are provided in a companion article (doi:10.1002/bimj.201300077).
Subjective Probability Distribution Elicitation in Cost Risk Analysis: A Review
2007-01-01
where reasonable, to counteract known biases in elicitation). 1 For the triangle distribution, the probability is set to zero outside the endpoints...probability is set to zero outside the endpoints, while between the endpoints the density rises linearly from the lower value to the most-likely values...Wheeler, T. A., S. C. Hora , W. R. Cramond, and S. D. Unwin, Analysis of Core Damage Frequency from Internal Events: Expert Judgment Elicitation
Shin, Seung Jun; Wu, Yichao
2014-07-01
This is a discussion of the papers: "Probability estimation with machine learning methods for dichotomous and multicategory outcome: Theory" by Jochen Kruppa, Yufeng Liu, Gérard Biau, Michael Kohler, Inke R. König, James D. Malley, and Andreas Ziegler; and "Probability estimation with machine learning methods for dichotomous and multicategory outcome: Applications" by Jochen Kruppa, Yufeng Liu, Hans-Christian Diener, Theresa Holste, Christian Weimar, Inke R. König, and Andreas Ziegler.
Seaver, D.A.; Stillwell, W.G.
1983-03-01
This report describes and evaluates several procedures for using expert judgment to estimate human-error probabilities (HEPs) in nuclear power plant operations. These HEPs are currently needed for several purposes, particularly for probabilistic risk assessments. Data do not exist for estimating these HEPs, so expert judgment can provide these estimates in a timely manner. Five judgmental procedures are described here: paired comparisons, ranking and rating, direct numerical estimation, indirect numerical estimation and multiattribute utility measurement. These procedures are evaluated in terms of several criteria: quality of judgments, difficulty of data collection, empirical support, acceptability, theoretical justification, and data processing. Situational constraints such as the number of experts available, the number of HEPs to be estimated, the time available, the location of the experts, and the resources available are discussed in regard to their implications for selecting a procedure for use.
Hubig, Michael; Muggenthaler, Holger; Mall, Gita
2014-05-01
Bayesian estimation applied to temperature based death time estimation was recently introduced as conditional probability distribution or CPD-method by Biermann and Potente. The CPD-method is useful, if there is external information that sets the boundaries of the true death time interval (victim last seen alive and found dead). CPD allows computation of probabilities for small time intervals of interest (e.g. no-alibi intervals of suspects) within the large true death time interval. In the light of the importance of the CPD for conviction or acquittal of suspects the present study identifies a potential error source. Deviations in death time estimates will cause errors in the CPD-computed probabilities. We derive formulae to quantify the CPD error as a function of input error. Moreover we observed the paradox, that in cases, in which the small no-alibi time interval is located at the boundary of the true death time interval, adjacent to the erroneous death time estimate, CPD-computed probabilities for that small no-alibi interval will increase with increasing input deviation, else the CPD-computed probabilities will decrease. We therefore advise not to use CPD if there is an indication of an error or a contra-empirical deviation in the death time estimates, that is especially, if the death time estimates fall out of the true death time interval, even if the 95%-confidence intervals of the estimate still overlap the true death time interval.
Waters, Martha; McKernan, Lauralynn; Maier, Andrew; Jayjock, Michael; Schaeffer, Val; Brosseau, Lisa
2015-01-01
The fundamental goal of this article is to describe, define, and analyze the components of the risk characterization process for occupational exposures. Current methods are described for the probabilistic characterization of exposure, including newer techniques that have increasing applications for assessing data from occupational exposure scenarios. In addition, since the probability of health effects reflects variability in the exposure estimate as well as the dose-response curve—the integrated considerations of variability surrounding both components of the risk characterization provide greater information to the occupational hygienist. Probabilistic tools provide a more informed view of exposure as compared to use of discrete point estimates for these inputs to the risk characterization process. Active use of such tools for exposure and risk assessment will lead to a scientifically supported worker health protection program. Understanding the bases for an occupational risk assessment, focusing on important sources of variability and uncertainty enables characterizing occupational risk in terms of a probability, rather than a binary decision of acceptable risk or unacceptable risk. A critical review of existing methods highlights several conclusions: (1) exposure estimates and the dose-response are impacted by both variability and uncertainty and a well-developed risk characterization reflects and communicates this consideration; (2) occupational risk is probabilistic in nature and most accurately considered as a distribution, not a point estimate; and (3) occupational hygienists have a variety of tools available to incorporate concepts of risk characterization into occupational health and practice. PMID:26302336
Moderate- and Large- Deviation Probabilities in Actuarial Risk Theory,
1988-06-01
Introduction to the Theory of Large Deviations, Springer-Verlag, New York. Thorin, 0. (1982), Probabilities of ruin, Scand. Actuar . Jour. 65-102. 25 *% 0 I S 0 S 3 9 I bJ\\~ S S I’ C..., S L2JI1C S ~
A double-observer approach for estimating detection probability and abundance from point counts
Nichols, J.D.; Hines, J.E.; Sauer, J.R.; Fallon, F.W.; Fallon, J.E.; Heglund, P.J.
2000-01-01
Although point counts are frequently used in ornithological studies, basic assumptions about detection probabilities often are untested. We apply a double-observer approach developed to estimate detection probabilities for aerial surveys (Cook and Jacobson 1979) to avian point counts. At each point count, a designated 'primary' observer indicates to another ('secondary') observer all birds detected. The secondary observer records all detections of the primary observer as well as any birds not detected by the primary observer. Observers alternate primary and secondary roles during the course of the survey. The approach permits estimation of observer-specific detection probabilities and bird abundance. We developed a set of models that incorporate different assumptions about sources of variation (e.g. observer, bird species) in detection probability. Seventeen field trials were conducted, and models were fit to the resulting data using program SURVIV. Single-observer point counts generally miss varying proportions of the birds actually present, and observer and bird species were found to be relevant sources of variation in detection probabilities. Overall detection probabilities (probability of being detected by at least one of the two observers) estimated using the double-observer approach were very high (>0.95), yielding precise estimates of avian abundance. We consider problems with the approach and recommend possible solutions, including restriction of the approach to fixed-radius counts to reduce the effect of variation in the effective radius of detection among various observers and to provide a basis for using spatial sampling to estimate bird abundance on large areas of interest. We believe that most questions meriting the effort required to carry out point counts also merit serious attempts to estimate detection probabilities associated with the counts. The double-observer approach is a method that can be used for this purpose.
Generalizations and Extensions of the Probability of Superiority Effect Size Estimator
ERIC Educational Resources Information Center
Ruscio, John; Gera, Benjamin Lee
2013-01-01
Researchers are strongly encouraged to accompany the results of statistical tests with appropriate estimates of effect size. For 2-group comparisons, a probability-based effect size estimator ("A") has many appealing properties (e.g., it is easy to understand, robust to violations of parametric assumptions, insensitive to outliers). We review…
Improving quality of sample entropy estimation for continuous distribution probability functions
NASA Astrophysics Data System (ADS)
Miśkiewicz, Janusz
2016-05-01
Entropy is a one of the key parameters characterizing state of system in statistical physics. Although, the entropy is defined for systems described by discrete and continuous probability distribution function (PDF), in numerous applications the sample entropy is estimated by a histogram, which, in fact, denotes that the continuous PDF is represented by a set of probabilities. Such a procedure may lead to ambiguities and even misinterpretation of the results. Within this paper, two possible general algorithms based on continuous PDF estimation are discussed in the application to the Shannon and Tsallis entropies. It is shown that the proposed algorithms may improve entropy estimation, particularly in the case of small data sets.
Brand, Matthias; Schiebener, Johannes; Pertl, Marie-Theres; Delazer, Margarete
2014-01-01
Recent models on decision making under risk conditions have suggested that numerical abilities are important ingredients of advantageous decision-making performance, but empirical evidence is still limited. The results of our first study show that logical reasoning and basic mental calculation capacities predict ratio processing and that ratio processing predicts decision making under risk. In the second study, logical reasoning together with executive functions predicted probability processing (numeracy and probability knowledge), and probability processing predicted decision making under risk. These findings suggest that increasing an individual's understanding of ratios and probabilities should lead to more advantageous decisions under risk conditions.
A removal model for estimating detection probabilities from point-count surveys
Farnsworth, G.L.; Pollock, K.H.; Nichols, J.D.; Simons, T.R.; Hines, J.E.; Sauer, J.R.
2000-01-01
We adapted a removal model to estimate detection probability during point count surveys. The model assumes one factor influencing detection during point counts is the singing frequency of birds. This may be true for surveys recording forest songbirds when most detections are by sound. The model requires counts to be divided into several time intervals. We used time intervals of 2, 5, and 10 min to develop a maximum-likelihood estimator for the detectability of birds during such surveys. We applied this technique to data from bird surveys conducted in Great Smoky Mountains National Park. We used model selection criteria to identify whether detection probabilities varied among species, throughout the morning, throughout the season, and among different observers. The overall detection probability for all birds was 75%. We found differences in detection probability among species. Species that sing frequently such as Winter Wren and Acadian Flycatcher had high detection probabilities (about 90%) and species that call infrequently such as Pileated Woodpecker had low detection probability (36%). We also found detection probabilities varied with the time of day for some species (e.g. thrushes) and between observers for other species. This method of estimating detectability during point count surveys offers a promising new approach to using count data to address questions of the bird abundance, density, and population trends.
Nichols, J.D.; Sauer, J.R.; Pollock, K.H.; Hestbeck, J.B.
1992-01-01
In stage-based demography, animals are often categorized into size (or mass) classes, and size-based probabilities of surviving and changing mass classes must be estimated before demographic analyses can be conducted. In this paper, we develop two procedures for the estimation of mass transition probabilities from capture-recapture data. The first approach uses a multistate capture-recapture model that is parameterized directly with the transition probabilities of interest. Maximum likelihood estimates are then obtained numerically using program SURVIV. The second approach involves a modification of Pollock's robust design. Estimation proceeds by conditioning on animals caught in a particualr class at time i, and then using closed models to estimate the number of these that are alive in other classes at i + 1. Both methods are illustrated by application to meadow vole, Microtus pennsylvanicus, capture-recapture data. The two methods produced reasonable estimates that were similar. Advantages of these two approaches include the directness of estimation, the absence of need for restrictive assumptions about the independence of survival and growth, the testability of assumptions, and the testability of related hypotheses of ecological interest (e.g., the hypothesis of temporal variation in transition probabilities).
Nonparametric maximum likelihood estimation of probability densities by penalty function methods
NASA Technical Reports Server (NTRS)
Demontricher, G. F.; Tapia, R. A.; Thompson, J. R.
1974-01-01
When it is known a priori exactly to which finite dimensional manifold the probability density function gives rise to a set of samples, the parametric maximum likelihood estimation procedure leads to poor estimates and is unstable; while the nonparametric maximum likelihood procedure is undefined. A very general theory of maximum penalized likelihood estimation which should avoid many of these difficulties is presented. It is demonstrated that each reproducing kernel Hilbert space leads, in a very natural way, to a maximum penalized likelihood estimator and that a well-known class of reproducing kernel Hilbert spaces gives polynomial splines as the nonparametric maximum penalized likelihood estimates.
NASA Astrophysics Data System (ADS)
Frigm, R.; Johnson, L.
The Probability of Collision (Pc) has become a universal metric and statement of on-orbit collision risk. Although several flavors of the computation exist and are well-documented in the literature, the basic calculation requires the same input: estimates for the position, position uncertainty, and sizes of the two objects involved. The Pc is used operationally to make decisions on whether a given conjunction poses significant collision risk to the primary object (or space asset of concern). It is also used to determine necessity and degree of mitigative action (typically in the form of an orbital maneuver) to be performed. The predicted post-maneuver Pc also informs the maneuver planning process into regarding the timing, direction, and magnitude of the maneuver needed to mitigate the collision risk. Although the data sources, techniques, decision calculus, and workflows vary for different agencies and organizations, they all have a common thread. The standard conjunction assessment and collision risk concept of operations (CONOPS) predicts conjunctions, assesses the collision risk (typically, via the Pc), and plans and executes avoidance activities for conjunctions as a discrete events. As the space debris environment continues to increase and improvements are made to remote sensing capabilities and sensitivities to detect, track, and predict smaller debris objects, the number of conjunctions will in turn continue to increase. The expected order-of-magnitude increase in the number of predicted conjunctions will challenge the paradigm of treating each conjunction as a discrete event. The challenge will not be limited to workload issues, such as manpower and computing performance, but also the ability for satellite owner/operators to successfully execute their mission while also managing on-orbit collision risk. Executing a propulsive maneuver occasionally can easily be absorbed into the mission planning and operations tempo; whereas, continuously planning evasive
Mossman, Douglas
2015-03-01
Probability plays a ubiquitous role in decision-making through a process in which we use data from groups of past outcomes to make inferences about new situations. Yet in recent years, many forensic mental health professionals have become persuaded that overly wide confidence intervals render actuarial risk assessment instruments virtually useless in individual assessments. If this were true, the mathematical properties of probabilistic judgments would preclude forensic clinicians from applying group-based findings about risk to individuals. As a consequence, actuarially based risk estimates might be barred from use in legal proceedings. Using a fictional scenario, I seek to show how group data have an obvious application to individual decisions. I also explain how misunderstanding the aims of risk assessment has led to mistakes about how, when, and why group data apply to individual instances. Although actuarially based statements about individuals' risk have many pitfalls, confidence intervals pose no barrier to using actuarial tools derived from group data to improve decision-making about individual instances.
Hoblitt, Richard P.; Scott, William E.
2011-01-01
In response to a request from the U.S. Department of Energy, we estimate the thickness of tephra accumulation that has an annual probability of 1 in 10,000 of being equaled or exceeded at the Hanford Site in south-central Washington State, where a project to build the Tank Waste Treatment and Immobilization Plant is underway. We follow the methodology of a 1987 probabilistic assessment of tephra accumulation in the Pacific Northwest. For a given thickness of tephra, we calculate the product of three probabilities: (1) the annual probability of an eruption producing 0.1 km3 (bulk volume) or more of tephra, (2) the probability that the wind will be blowing toward the Hanford Site, and (3) the probability that tephra accumulations will equal or exceed the given thickness at a given distance. Mount St. Helens, which lies about 200 km upwind from the Hanford Site, has been the most prolific source of tephra fallout among Cascade volcanoes in the recent geologic past and its annual eruption probability based on this record (0.008) dominates assessment of future tephra falls at the site. The probability that the prevailing wind blows toward Hanford from Mount St. Helens is 0.180. We estimate exceedance probabilities of various thicknesses of tephra fallout from an analysis of 14 eruptions of the size expectable from Mount St. Helens and for which we have measurements of tephra fallout at 200 km. The result is that the estimated thickness of tephra accumulation that has an annual probability of 1 in 10,000 of being equaled or exceeded is about 10 centimeters. It is likely that this thickness is a maximum estimate because we used conservative estimates of eruption and wind probabilities and because the 14 deposits we used probably provide an over-estimate. The use of deposits in this analysis that were mostly compacted by the time they were studied and measured implies that the bulk density of the tephra fallout we consider here is in the range of 1,000-1,250 kg/m3. The
Gerhardt, Andrea; Scharf, Rüdiger E; Greer, Ian A; Zotz, Rainer B
2016-09-09
Venous thromboembolism (VTE) is a leading cause of maternal mortality. Few studies have evaluated the individual risk of gestational VTE associated with heritable thrombophilia and current recommendations for antenatal thromboprophylaxis in women with severe thrombophilia such as homozygous factor V Leiden mutation (FVL) depend on a positive family history of VTE. To better stratify thromboprophylaxis in pregnancy, we aimed to estimate the individual probability (absolute risk) of gestational VTE associated with thrombophilia and whether these risk factors are independent of a family history of VTE in first-degree relatives. We studied 243 women with first VTE during pregnancy and the puerperium, and 243 age-matched normal women. Baseline incidence of VTE of 1:483 pregnancies in women ≥35 years and 1:741 deliveries in women <35 years was assumed, according to a recent population-based study. In women ≥35 years [<35 years], the individual probability of gestational VTE was: 0.7% [0.5%] for heterozygous FVL; 3.4% [2.2%], for homozygous FVL; 0.6% [0.4%], for heterozygous prothrombin G20210A; 8.2% [5.5%] for compound heterozygotes for FVL and prothrombin G20210A; 9.0% [6.1%] for antithrombin deficiency; 1.1% [0.7%] for protein C deficiency; and 1.0% [0.7%] for protein S deficiency These results were independent of a positive family history of VTE. We provide evidence that unselected women with these thrombophilias have an increased risk of gestational VTE independent of a positive family history of VTE. In contrast to current guidelines, these data suggest that women with high-risk thrombophilia should be considered for antenatal thromboprophylaxis regardless of family history of VTE.
Multifractals embedded in short time series: An unbiased estimation of probability moment
NASA Astrophysics Data System (ADS)
Qiu, Lu; Yang, Tianguang; Yin, Yanhua; Gu, Changgui; Yang, Huijie
2016-12-01
An exact estimation of probability moments is the base for several essential concepts, such as the multifractals, the Tsallis entropy, and the transfer entropy. By means of approximation theory we propose a new method called factorial-moment-based estimation of probability moments. Theoretical prediction and computational results show that it can provide us an unbiased estimation of the probability moments of continuous order. Calculations on probability redistribution model verify that it can extract exactly multifractal behaviors from several hundred recordings. Its powerfulness in monitoring evolution of scaling behaviors is exemplified by two empirical cases, i.e., the gait time series for fast, normal, and slow trials of a healthy volunteer, and the closing price series for Shanghai stock market. By using short time series with several hundred lengths, a comparison with the well-established tools displays significant advantages of its performance over the other methods. The factorial-moment-based estimation can evaluate correctly the scaling behaviors in a scale range about three generations wider than the multifractal detrended fluctuation analysis and the basic estimation. The estimation of partition function given by the wavelet transform modulus maxima has unacceptable fluctuations. Besides the scaling invariance focused in the present paper, the proposed factorial moment of continuous order can find its various uses, such as finding nonextensive behaviors of a complex system and reconstructing the causality relationship network between elements of a complex system.
A removal model for estimating detection probabilities from point-count surveys
Farnsworth, G.L.; Pollock, K.H.; Nichols, J.D.; Simons, T.R.; Hines, J.E.; Sauer, J.R.
2002-01-01
Use of point-count surveys is a popular method for collecting data on abundance and distribution of birds. However, analyses of such data often ignore potential differences in detection probability. We adapted a removal model to directly estimate detection probability during point-count surveys. The model assumes that singing frequency is a major factor influencing probability of detection when birds are surveyed using point counts. This may be appropriate for surveys in which most detections are by sound. The model requires counts to be divided into several time intervals. Point counts are often conducted for 10 min, where the number of birds recorded is divided into those first observed in the first 3 min, the subsequent 2 min, and the last 5 min. We developed a maximum-likelihood estimator for the detectability of birds recorded during counts divided into those intervals. This technique can easily be adapted to point counts divided into intervals of any length. We applied this method to unlimited-radius counts conducted in Great Smoky Mountains National Park. We used model selection criteria to identify whether detection probabilities varied among species, throughout the morning, throughout the season, and among different observers. We found differences in detection probability among species. Species that sing frequently such as Winter Wren (Troglodytes troglodytes) and Acadian Flycatcher (Empidonax virescens) had high detection probabilities (~90%) and species that call infrequently such as Pileated Woodpecker (Dryocopus pileatus) had low detection probability (36%). We also found detection probabilities varied with the time of day for some species (e.g. thrushes) and between observers for other species. We used the same approach to estimate detection probability and density for a subset of the observations with limited-radius point counts.
Using of bayesian networks to estimate the probability of "NATECH" scenario occurrence
NASA Astrophysics Data System (ADS)
Dobes, Pavel; Dlabka, Jakub; Jelšovská, Katarína; Polorecká, Mária; Baudišová, Barbora; Danihelka, Pavel
2015-04-01
In the twentieth century, implementation of Bayesian statistics and probability was not much used (may be it wasn't a preferred approach) in the area of natural and industrial risk analysis and management. Neither it was used within analysis of so called NATECH accidents (chemical accidents triggered by natural events, such as e.g. earthquakes, floods, lightning etc.; ref. E. Krausmann, 2011, doi:10.5194/nhess-11-921-2011). Main role, from the beginning, played here so called "classical" frequentist probability (ref. Neyman, 1937), which rely up to now especially on the right/false results of experiments and monitoring and didn't enable to count on expert's beliefs, expectations and judgements (which is, on the other hand, one of the once again well known pillars of Bayessian approach to probability). In the last 20 or 30 years, there is possible to observe, through publications and conferences, the Renaissance of Baysssian statistics into many scientific disciplines (also into various branches of geosciences). The necessity of a certain level of trust in expert judgment within risk analysis is back? After several decades of development on this field, it could be proposed following hypothesis (to be checked): "We couldn't estimate probabilities of complex crisis situations and their TOP events (many NATECH events could be classified as crisis situations or emergencies), only by classical frequentist approach, but also by using of Bayessian approach (i.e. with help of prestaged Bayessian Network including expert belief and expectation as well as classical frequentist inputs). Because - there is not always enough quantitative information from monitoring of historical emergencies, there could be several dependant or independant variables necessary to consider and in generally - every emergency situation always have a little different run." In this topic, team of authors presents its proposal of prestaged typized Bayessian network model for specified NATECH scenario
Estimating the Probability of Asteroid Collision with the Earth by the Monte Carlo Method
NASA Astrophysics Data System (ADS)
Chernitsov, A. M.; Tamarov, V. A.; Barannikov, E. A.
2016-09-01
The commonly accepted method of estimating the probability of asteroid collision with the Earth is investigated on an example of two fictitious asteroids one of which must obviously collide with the Earth and the second must pass by at a dangerous distance from the Earth. The simplest Kepler model of motion is used. Confidence regions of asteroid motion are estimated by the Monte Carlo method. Two variants of constructing the confidence region are considered: in the form of points distributed over the entire volume and in the form of points mapped onto the boundary surface. The special feature of the multidimensional point distribution in the first variant of constructing the confidence region that can lead to zero probability of collision for bodies that collide with the Earth is demonstrated. The probability estimates obtained for even considerably smaller number of points in the confidence region determined by its boundary surface are free from this disadvantage.
Austin, Peter C
2016-12-30
Propensity score methods are used to reduce the effects of observed confounding when using observational data to estimate the effects of treatments or exposures. A popular method of using the propensity score is inverse probability of treatment weighting (IPTW). When using this method, a weight is calculated for each subject that is equal to the inverse of the probability of receiving the treatment that was actually received. These weights are then incorporated into the analyses to minimize the effects of observed confounding. Previous research has found that these methods result in unbiased estimation when estimating the effect of treatment on survival outcomes. However, conventional methods of variance estimation were shown to result in biased estimates of standard error. In this study, we conducted an extensive set of Monte Carlo simulations to examine different methods of variance estimation when using a weighted Cox proportional hazards model to estimate the effect of treatment. We considered three variance estimation methods: (i) a naïve model-based variance estimator; (ii) a robust sandwich-type variance estimator; and (iii) a bootstrap variance estimator. We considered estimation of both the average treatment effect and the average treatment effect in the treated. We found that the use of a bootstrap estimator resulted in approximately correct estimates of standard errors and confidence intervals with the correct coverage rates. The other estimators resulted in biased estimates of standard errors and confidence intervals with incorrect coverage rates. Our simulations were informed by a case study examining the effect of statin prescribing on mortality. © 2016 The Authors. Statistics in Medicine published by John Wiley & Sons Ltd.
Relating space radiation environments to risk estimates
Curtis, S.B.
1991-10-01
This lecture will provide a bridge from the physical energy or LET spectra as might be calculated in an organ to the risk of carcinogenesis, a particular concern for extended missions to the moon or beyond to Mars. Topics covered will include (1) LET spectra expected from galactic cosmic rays, (2) probabilities that individual cell nuclei in the body will be hit by heavy galactic cosmic ray particles, (3) the conventional methods of calculating risks from a mixed environment of high and low LET radiation, (4) an alternate method which provides certain advantages using fluence-related risk coefficients (risk cross sections), and (5) directions for future research and development of these ideas.
van der Hoop, Julie M; Vanderlaan, Angelia S M; Taggart, Christopher T
2012-10-01
Vessel strikes are the primary source of known mortality for the endangered North Atlantic right whale (Eubalaena glacialis). Multi-institutional efforts to reduce mortality associated with vessel strikes include vessel-routing amendments such as the International Maritime Organization voluntary "area to be avoided" (ATBA) in the Roseway Basin right whale feeding habitat on the southwestern Scotian Shelf. Though relative probabilities of lethal vessel strikes have been estimated and published, absolute probabilities remain unknown. We used a modeling approach to determine the regional effect of the ATBA, by estimating reductions in the expected number of lethal vessel strikes. This analysis differs from others in that it explicitly includes a spatiotemporal analysis of real-time transits of vessels through a population of simulated, swimming right whales. Combining automatic identification system (AIS) vessel navigation data and an observationally based whale movement model allowed us to determine the spatial and temporal intersection of vessels and whales, from which various probability estimates of lethal vessel strikes are derived. We estimate one lethal vessel strike every 0.775-2.07 years prior to ATBA implementation, consistent with and more constrained than previous estimates of every 2-16 years. Following implementation, a lethal vessel strike is expected every 41 years. When whale abundance is held constant across years, we estimate that voluntary vessel compliance with the ATBA results in an 82% reduction in the per capita rate of lethal strikes; very similar to a previously published estimate of 82% reduction in the relative risk of a lethal vessel strike. The models we developed can inform decision-making and policy design, based on their ability to provide absolute, population-corrected, time-varying estimates of lethal vessel strikes, and they are easily transported to other regions and situations.
Delavande, Adeline; Rohwedder, Susann
2013-01-01
Cross-country comparisons of differential survival by socioeconomic status (SES) are useful in many domains. Yet, to date, such studies have been rare. Reliably estimating differential survival in a single country has been challenging because it requires rich panel data with a large sample size. Cross-country estimates have proven even more difficult because the measures of SES need to be comparable internationally. We present an alternative method for acquiring information on differential survival by SES. Rather than using observations of actual survival, we relate individuals’ subjective probabilities of survival to SES variables in cross section. To show that subjective survival probabilities are informative proxies for actual survival when estimating differential survival, we compare estimates of differential survival based on actual survival with estimates based on subjective probabilities of survival for the same sample. The results are remarkably similar. We then use this approach to compare differential survival by SES for 10 European countries and the United States. Wealthier people have higher survival probabilities than those who are less wealthy, but the strength of the association differs across countries. Nations with a smaller gradient appear to be Belgium, France, and Italy, while the United States, England, and Sweden appear to have a larger gradient. PMID:22042664
Alvares, N; Lambert, H
2007-02-07
The Federal Aviation Administration (FAA) identified 17 accidents that may have resulted from fuel tank explosions on commercial aircraft from 1959 to 2001. Seven events involved JP 4 or JP 4/Jet A mixtures that are no longer used for commercial aircraft fuel. The remaining 10 events involved Jet A or Jet A1 fuels that are in current use by the commercial aircraft industry. Four fuel tank explosions occurred in center wing tanks (CWTs) where on-board appliances can potentially transfer heat to the tank. These tanks are designated as ''Heated Center Wing Tanks'' (HCWT). Since 1996, the FAA has significantly increased the rate at which it has mandated airworthiness directives (ADs) directed at elimination of ignition sources. This effort includes the adoption, in 2001, of Special Federal Aviation Regulation 88 of 14 CFR part 21 (SFAR 88 ''Fuel Tank System Fault Tolerance Evaluation Requirements''). This paper addresses SFAR 88 effectiveness in reducing HCWT ignition source probability. Our statistical analysis, relating the occurrence of both on-ground and in-flight HCWT explosions to the cumulative flight hours of commercial passenger aircraft containing HCWT's reveals that the best estimate of HCWT explosion rate is 1 explosion in 1.4 x 10{sup 8} flight hours. Based on an analysis of SFAR 88 by Sandia National Laboratories and our independent analysis, SFAR 88 reduces current risk of historical HCWT explosion by at least a factor of 10, thus meeting an FAA risk criteria of 1 accident in billion flight hours. This paper also surveys and analyzes parameters for Jet A fuel ignition in HCWT's. Because of the paucity of in-flight HCWT explosions, we conclude that the intersection of the parameters necessary and sufficient to result in an HCWT explosion with sufficient overpressure to rupture the HCWT is extremely rare.
NASA Astrophysics Data System (ADS)
Haigh, Ivan D.; MacPherson, Leigh R.; Mason, Matthew S.; Wijeratne, E. M. S.; Pattiaratchi, Charitha B.; Crompton, Ryan P.; George, Steve
2014-01-01
The incidence of major storm surges in the last decade have dramatically emphasized the immense destructive capabilities of extreme water level events, particularly when driven by severe tropical cyclones. Given this risk, it is vitally important that the exceedance probabilities of extreme water levels are accurately evaluated to inform risk-based flood and erosion management, engineering and for future land-use planning and to ensure the risk of catastrophic structural failures due to under-design or expensive wastes due to over-design are minimised. Australia has a long history of coastal flooding from tropical cyclones. Using a novel integration of two modeling techniques, this paper provides the first estimates of present day extreme water level exceedance probabilities around the whole coastline of Australia, and the first estimates that combine the influence of astronomical tides, storm surges generated by both extra-tropical and tropical cyclones, and seasonal and inter-annual variations in mean sea level. Initially, an analysis of tide gauge records has been used to assess the characteristics of tropical cyclone-induced surges around Australia. However, given the dearth (temporal and spatial) of information around much of the coastline, and therefore the inability of these gauge records to adequately describe the regional climatology, an observationally based stochastic tropical cyclone model has been developed to synthetically extend the tropical cyclone record to 10,000 years. Wind and pressure fields derived for these synthetically generated events have then been used to drive a hydrodynamic model of the Australian continental shelf region with annual maximum water levels extracted to estimate exceedance probabilities around the coastline. To validate this methodology, selected historic storm surge events have been simulated and resultant storm surges compared with gauge records. Tropical cyclone induced exceedance probabilities have been combined with
Crawford, John R; Garthwaite, Paul H; Betkowska, Karolina
2009-05-01
Most neuropsychologists are aware that, given the specificity and sensitivity of a test and an estimate of the base rate of a disorder, Bayes' theorem can be used to provide a post-test probability for the presence of the disorder given a positive test result (and a post-test probability for the absence of a disorder given a negative result). However, in the standard application of Bayes' theorem the three quantities (sensitivity, specificity, and the base rate) are all treated as fixed, known quantities. This is very unrealistic as there may be considerable uncertainty over these quantities and therefore even greater uncertainty over the post-test probability. Methods of obtaining interval estimates on the specificity and sensitivity of a test are set out. In addition, drawing and extending upon work by Mossman and Berger (2001), a Monte Carlo method is used to obtain interval estimates for post-test probabilities. All the methods have been implemented in a computer program, which is described and made available (www.abdn.ac.uk/~psy086/dept/BayesPTP.htm). When objective data on the base rate are lacking (or have limited relevance to the case at hand) the program elicits opinion for the pre-test probability.
2012-09-01
incorporates macro economic and policy level information. In the first step the conditional probabilities of staying or leaving the Navy are estimated...accommodates time dependent information, cohort information, censoring problems with the data as well as incorporating macro economic and policy level ...1 Introducing the Individual Level Information (Covariates
Mediators of the Availability Heuristic in Probability Estimates of Future Events.
ERIC Educational Resources Information Center
Levi, Ariel S.; Pryor, John B.
Individuals often estimate the probability of future events by the ease with which they can recall or cognitively construct relevant instances. Previous research has not precisely identified the cognitive processes mediating this "availability heuristic." Two potential mediators (imagery of the event, perceived reasons or causes for the…
Waits, L P; Luikart, G; Taberlet, P
2001-01-01
Individual identification using DNA fingerprinting methods is emerging as a critical tool in conservation genetics and molecular ecology. Statistical methods that estimate the probability of sampling identical genotypes using theoretical equations generally assume random associations between alleles within and among loci. These calculations are probably inaccurate for many animal and plant populations due to population substructure. We evaluated the accuracy of a probability of identity (P(ID)) estimation by comparing the observed and expected P(ID), using large nuclear DNA microsatellite data sets from three endangered species: the grey wolf (Canis lupus), the brown bear (Ursus arctos), and the Australian northern hairy-nosed wombat (Lasiorinyus krefftii). The theoretical estimates of P(ID) were consistently lower than the observed P(ID), and can differ by as much as three orders of magnitude. To help researchers and managers avoid potential problems associated with this bias, we introduce an equation for P(ID) between sibs. This equation provides an estimator that can be used as a conservative upper bound for the probability of observing identical multilocus genotypes between two individuals sampled from a population. We suggest computing the actual observed P(ID) when possible and give general guidelines for the number of codominant and dominant marker loci required to achieve a reasonably low P(ID) (e.g. 0.01-0.0001).
2013-03-01
Presented to the Faculty Department of Operational Sciences Graduate School of Engineering and Management Air Force Institute of Technology Air...University Air Education and Training Command In Partial Fulfillment of the Requirements for the Degree of Master of Science in Operations ...to estimate these unknown multinomial success probabilities, , for each of the systems [17]. Bechhofer and Sobel [18] made use of multinomial
Estimating twin concordance for bivariate competing risks twin data.
Scheike, Thomas H; Holst, Klaus K; Hjelmborg, Jacob B
2014-03-30
For twin time-to-event data, we consider different concordance probabilities, such as the casewise concordance that are routinely computed as a measure of the lifetime dependence/correlation for specific diseases. The concordance probability here is the probability that both twins have experienced the event of interest. Under the assumption that both twins are censored at the same time, we show how to estimate this probability in the presence of right censoring, and as a consequence, we can then estimate the casewise twin concordance. In addition, we can model the magnitude of within pair dependence over time, and covariates may be further influential on the marginal risk and dependence structure. We establish the estimators large sample properties and suggest various tests, for example, for inferring familial influence. The method is demonstrated and motivated by specific twin data on cancer events with the competing risk death. We thus aim to quantify the degree of dependence through the casewise concordance function and show a significant genetic component.
ERIC Educational Resources Information Center
Harris, Adam J. L.; Corner, Adam
2011-01-01
Verbal probability expressions are frequently used to communicate risk and uncertainty. The Intergovernmental Panel on Climate Change (IPCC), for example, uses them to convey risks associated with climate change. Given the potential for human action to mitigate future environmental risks, it is important to understand how people respond to these…
NASA Astrophysics Data System (ADS)
Boslough, M.
2011-12-01
Climate-related uncertainty is traditionally presented as an error bar, but it is becoming increasingly common to express it in terms of a probability density function (PDF). PDFs are a necessary component of probabilistic risk assessments, for which simple "best estimate" values are insufficient. Many groups have generated PDFs for climate sensitivity using a variety of methods. These PDFs are broadly consistent, but vary significantly in their details. One axiom of the verification and validation community is, "codes don't make predictions, people make predictions." This is a statement of the fact that subject domain experts generate results using assumptions within a range of epistemic uncertainty and interpret them according to their expert opinion. Different experts with different methods will arrive at different PDFs. For effective decision support, a single consensus PDF would be useful. We suggest that market methods can be used to aggregate an ensemble of opinions into a single distribution that expresses the consensus. Prediction markets have been shown to be highly successful at forecasting the outcome of events ranging from elections to box office returns. In prediction markets, traders can take a position on whether some future event will or will not occur. These positions are expressed as contracts that are traded in a double-action market that aggregates price, which can be interpreted as a consensus probability that the event will take place. Since climate sensitivity cannot directly be measured, it cannot be predicted. However, the changes in global mean surface temperature are a direct consequence of climate sensitivity, changes in forcing, and internal variability. Viable prediction markets require an undisputed event outcome on a specific date. Climate-related markets exist on Intrade.com, an online trading exchange. One such contract is titled "Global Temperature Anomaly for Dec 2011 to be greater than 0.65 Degrees C." Settlement is based
O'Connell, Allan F.; Talancy, Neil W.; Bailey, Larissa L.; Sauer, John R.; Cook, Robert; Gilbert, Andrew T.
2006-01-01
Large-scale, multispecies monitoring programs are widely used to assess changes in wildlife populations but they often assume constant detectability when documenting species occurrence. This assumption is rarely met in practice because animal populations vary across time and space. As a result, detectability of a species can be influenced by a number of physical, biological, or anthropogenic factors (e.g., weather, seasonality, topography, biological rhythms, sampling methods). To evaluate some of these influences, we estimated site occupancy rates using species-specific detection probabilities for meso- and large terrestrial mammal species on Cape Cod, Massachusetts, USA. We used model selection to assess the influence of different sampling methods and major environmental factors on our ability to detect individual species. Remote cameras detected the most species (9), followed by cubby boxes (7) and hair traps (4) over a 13-month period. Estimated site occupancy rates were similar among sampling methods for most species when detection probabilities exceeded 0.15, but we question estimates obtained from methods with detection probabilities between 0.05 and 0.15, and we consider methods with lower probabilities unacceptable for occupancy estimation and inference. Estimated detection probabilities can be used to accommodate variation in sampling methods, which allows for comparison of monitoring programs using different protocols. Vegetation and seasonality produced species-specific differences in detectability and occupancy, but differences were not consistent within or among species, which suggests that our results should be considered in the context of local habitat features and life history traits for the target species. We believe that site occupancy is a useful state variable and suggest that monitoring programs for mammals using occupancy data consider detectability prior to making inferences about species distributions or population change.
Langtimm, C.A.; O'Shea, T.J.; Pradel, R.; Beck, C.A.
1998-01-01
The population dynamics of large, long-lived mammals are particularly sensitive to changes in adult survival. Understanding factors affecting survival patterns is therefore critical for developing and testing theories of population dynamics and for developing management strategies aimed at preventing declines or extinction in such taxa. Few studies have used modern analytical approaches for analyzing variation and testing hypotheses about survival probabilities in large mammals. This paper reports a detailed analysis of annual adult survival in the Florida manatee (Trichechus manatus latirostris), an endangered marine mammal, based on a mark-recapture approach. Natural and boat-inflicted scars distinctively 'marked' individual manatees that were cataloged in a computer-based photographic system. Photo-documented resightings provided 'recaptures.' Using open population models, annual adult-survival probabilities were estimated for manatees observed in winter in three areas of Florida: Blue Spring, Crystal River, and the Atlantic coast. After using goodness-of-fit tests in Program RELEASE to search for violations of the assumptions of mark-recapture analysis, survival and sighting probabilities were modeled under several different biological hypotheses with Program SURGE. Estimates of mean annual probability of sighting varied from 0.948 for Blue Spring to 0.737 for Crystal River and 0.507 for the Atlantic coast. At Crystal River and Blue Spring, annual survival probabilities were best estimated as constant over the study period at 0.96 (95% CI = 0.951-0.975 and 0.900-0.985, respectively). On the Atlantic coast, where manatees are impacted more by human activities, annual survival probabilities had a significantly lower mean estimate of 0.91 (95% CI = 0.887-0.926) and varied unpredictably over the study period. For each study area, survival did not differ between sexes and was independent of relative adult age. The high constant adult-survival probabilities estimated
PIGS: improved estimates of identity-by-descent probabilities by probabilistic IBD graph sampling
2015-01-01
Identifying segments in the genome of different individuals that are identical-by-descent (IBD) is a fundamental element of genetics. IBD data is used for numerous applications including demographic inference, heritability estimation, and mapping disease loci. Simultaneous detection of IBD over multiple haplotypes has proven to be computationally difficult. To overcome this, many state of the art methods estimate the probability of IBD between each pair of haplotypes separately. While computationally efficient, these methods fail to leverage the clique structure of IBD resulting in less powerful IBD identification, especially for small IBD segments. We develop a hybrid approach (PIGS), which combines the computational efficiency of pairwise methods with the power of multiway methods. It leverages the IBD graph structure to compute the probability of IBD conditional on all pairwise estimates simultaneously. We show via extensive simulations and analysis of real data that our method produces a substantial increase in the number of identified small IBD segments. PMID:25860540
Estimating site occupancy rates when detection probabilities are less than one
MacKenzie, D.I.; Nichols, J.D.; Lachman, G.B.; Droege, S.; Royle, J. Andrew; Langtimm, C.A.
2002-01-01
Nondetection of a species at a site does not imply that the species is absent unless the probability of detection is 1. We propose a model and likelihood-based method for estimating site occupancy rates when detection probabilities are 0.3). We estimated site occupancy rates for two anuran species at 32 wetland sites in Maryland, USA, from data collected during 2000 as part of an amphibian monitoring program, Frogwatch USA. Site occupancy rates were estimated as 0.49 for American toads (Bufo americanus), a 44% increase over the proportion of sites at which they were actually observed, and as 0.85 for spring peepers (Pseudacris crucifer), slightly above the observed proportion of 0.83.
Empirical estimation of the conditional probability of natech events within the United States.
Santella, Nicholas; Steinberg, Laura J; Aguirra, Gloria Andrea
2011-06-01
Natural disasters are the cause of a sizeable number of hazmat releases, referred to as "natechs." An enhanced understanding of natech probability, allowing for predictions of natech occurrence, is an important step in determining how industry and government should mitigate natech risk. This study quantifies the conditional probabilities of natechs at TRI/RMP and SICS 1311 facilities given the occurrence of hurricanes, earthquakes, tornadoes, and floods. During hurricanes, a higher probability of releases was observed due to storm surge (7.3 releases per 100 TRI/RMP facilities exposed vs. 6.2 for SIC 1311) compared to category 1-2 hurricane winds (5.6 TRI, 2.6 SIC 1311). Logistic regression confirms the statistical significance of the greater propensity for releases at RMP/TRI facilities, and during some hurricanes, when controlling for hazard zone. The probability of natechs at TRI/RMP facilities during earthquakes increased from 0.1 releases per 100 facilities at MMI V to 21.4 at MMI IX. The probability of a natech at TRI/RMP facilities within 25 miles of a tornado was small (∼0.025 per 100 facilities), reflecting the limited area directly affected by tornadoes. Areas inundated during flood events had a probability of 1.1 releases per 100 facilities but demonstrated widely varying natech occurrence during individual events, indicating that factors not quantified in this study such as flood depth and speed are important for predicting flood natechs. These results can inform natech risk analysis, aid government agencies responsible for planning response and remediation after natural disasters, and should be useful in raising awareness of natech risk within industry.
On the Estimation of Detection Probabilities for Sampling Stream-Dwelling Fishes.
Peterson, James T.
1999-11-01
To examine the adequacy of fish probability of detection estimates, I examined distributional properties of survey and monitoring data for bull trout (Salvelinus confluentus), brook trout (Salvelinus fontinalis), westslope cutthroat trout (Oncorhynchus clarki lewisi), chinook salmon parr (Oncorhynchus tshawytscha), and steelhead /redband trout (Oncorhynchus mykiss spp.), from 178 streams in the Interior Columbia River Basin. Negative binomial dispersion parameters varied considerably among species and streams, but were significantly (P<0.05) positively related to fish density. Across streams, the variances in fish abundances differed greatly among species and indicated that the data for all species were overdispersed with respect to the Poisson (i.e., the variances exceeded the means). This significantly affected Poisson probability of detection estimates, which were the highest across species and were, on average, 3.82, 2.66, and 3.47 times greater than baseline values. Required sample sizes for species detection at the 95% confidence level were also lowest for the Poisson, which underestimated sample size requirements an average of 72% across species. Negative binomial and Poisson-gamma probability of detection and sample size estimates were more accurate than the Poisson and generally less than 10% from baseline values. My results indicate the Poisson and binomial assumptions often are violated, which results in probability of detection estimates that are biased high and sample size estimates that are biased low. To increase the accuracy of these estimates, I recommend that future studies use predictive distributions than can incorporate multiple sources of uncertainty or excess variance and that all distributional assumptions be explicitly tested.
Submarine tower escape decompression sickness risk estimation.
Loveman, G A M; Seddon, E M; Thacker, J C; Stansfield, M R; Jurd, K M
2014-01-01
Actions to enhance survival in a distressed submarine (DISSUB) scenario may be guided in part by knowledge of the likely risk of decompression sickness (DCS) should the crew attempt tower escape. A mathematical model for DCS risk estimation has been calibrated against DCS outcome data from 3,738 exposures of either men or goats to raised pressure. Body mass was used to scale DCS risk. The calibration data included more than 1,000 actual or simulated submarine escape exposures and no exposures with substantial staged decompression. Cases of pulmonary barotrauma were removed from the calibration data. The calibrated model was used to estimate the likelihood of DCS occurrence following submarine escape from the United Kingdom Royal Navy tower escape system. Where internal DISSUB pressure remains at - 0.1 MPa, escape from DISSUB depths < 200 meters is estimated to have DCS risk < 6%. Saturation at raised DISSUB pressure markedly increases risk, with > 60% DCS risk predicted for a 200-meter escape from saturation at 0.21 MPa. Using the calibrated model to predict DCS for direct ascent from saturation gives similar risk estimates to other published models.
Michael, Andrew J.
2012-01-01
Estimates of the probability that an ML 4.8 earthquake, which occurred near the southern end of the San Andreas fault on 24 March 2009, would be followed by an M 7 mainshock over the following three days vary from 0.0009 using a Gutenberg–Richter model of aftershock statistics (Reasenberg and Jones, 1989) to 0.04 using a statistical model of foreshock behavior and long‐term estimates of large earthquake probabilities, including characteristic earthquakes (Agnew and Jones, 1991). I demonstrate that the disparity between the existing approaches depends on whether or not they conform to Gutenberg–Richter behavior. While Gutenberg–Richter behavior is well established over large regions, it could be violated on individual faults if they have characteristic earthquakes or over small areas if the spatial distribution of large‐event nucleations is disproportional to the rate of smaller events. I develop a new form of the aftershock model that includes characteristic behavior and combines the features of both models. This new model and the older foreshock model yield the same results when given the same inputs, but the new model has the advantage of producing probabilities for events of all magnitudes, rather than just for events larger than the initial one. Compared with the aftershock model, the new model has the advantage of taking into account long‐term earthquake probability models. Using consistent parameters, the probability of an M 7 mainshock on the southernmost San Andreas fault is 0.0001 for three days from long‐term models and the clustering probabilities following the ML 4.8 event are 0.00035 for a Gutenberg–Richter distribution and 0.013 for a characteristic‐earthquake magnitude–frequency distribution. Our decisions about the existence of characteristic earthquakes and how large earthquakes nucleate have a first‐order effect on the probabilities obtained from short‐term clustering models for these large events.
A maximum a posteriori probability time-delay estimation for seismic signals
NASA Astrophysics Data System (ADS)
Carrier, A.; Got, J.-L.
2014-09-01
Cross-correlation and cross-spectral time delays often exhibit strong outliers due to ambiguities or cycle jumps in the correlation function. Their number increases when signal-to-noise, signal similarity or spectral bandwidth decreases. Such outliers heavily determine the time-delay probability density function and the results of further computations (e.g. double-difference location and tomography) using these time delays. In the present research we expressed cross-correlation as a function of the squared difference between signal amplitudes and show that they are closely related. We used this difference as a cost function whose minimum is reached when signals are aligned. Ambiguities may be removed in this function by using a priori information. We propose using the traveltime difference as a priori time-delay information. By modelling the probability density function of the traveltime difference by a Cauchy distribution and the probability density function of the data (differences of seismic signal amplitudes) by a Laplace distribution we were able to find explicitly the time-delay a posteriori probability density function. The location of the maximum of this a posteriori probability density function is the maximum a posteriori time-delay estimation for earthquake signals. Using this estimation to calculate time delays for earthquakes on the south flank of Kilauea statistically improved the cross-correlation time-delay estimation for these data and resulted in successful double-difference relocation for an increased number of earthquakes. This robust time-delay estimation improves the spatiotemporal resolution of seismicity rates in the south flank of Kilauea.
Simplified Computation for Nonparametric Windows Method of Probability Density Function Estimation.
Joshi, Niranjan; Kadir, Timor; Brady, Michael
2011-08-01
Recently, Kadir and Brady proposed a method for estimating probability density functions (PDFs) for digital signals which they call the Nonparametric (NP) Windows method. The method involves constructing a continuous space representation of the discrete space and sampled signal by using a suitable interpolation method. NP Windows requires only a small number of observed signal samples to estimate the PDF and is completely data driven. In this short paper, we first develop analytical formulae to obtain the NP Windows PDF estimates for 1D, 2D, and 3D signals, for different interpolation methods. We then show that the original procedure to calculate the PDF estimate can be significantly simplified and made computationally more efficient by a judicious choice of the frame of reference. We have also outlined specific algorithmic details of the procedures enabling quick implementation. Our reformulation of the original concept has directly demonstrated a close link between the NP Windows method and the Kernel Density Estimator.
Optimal estimation for regression models on τ-year survival probability.
Kwak, Minjung; Kim, Jinseog; Jung, Sin-Ho
2015-01-01
A logistic regression method can be applied to regressing the [Formula: see text]-year survival probability to covariates, if there are no censored observations before time [Formula: see text]. But if some observations are incomplete due to censoring before time [Formula: see text], then the logistic regression cannot be applied. Jung (1996) proposed to modify the score function for logistic regression to accommodate the right-censored observations. His modified score function, motivated for a consistent estimation of regression parameters, becomes a regular logistic score function if no observations are censored before time [Formula: see text]. In this article, we propose a modification of Jung's estimating function for an optimal estimation for the regression parameters in addition to consistency. We prove that the optimal estimator is more efficient than Jung's estimator. This theoretical comparison is illustrated with a real example data analysis and simulations.
Impact of microbial count distributions on human health risk estimates.
Duarte, A S R; Nauta, M J
2015-02-16
Quantitative microbiological risk assessment (QMRA) is influenced by the choice of the probability distribution used to describe pathogen concentrations, as this may eventually have a large effect on the distribution of doses at exposure. When fitting a probability distribution to microbial enumeration data, several factors may have an impact on the accuracy of that fit. Analysis of the best statistical fits of different distributions alone does not provide a clear indication of the impact in terms of risk estimates. Thus, in this study we focus on the impact of fitting microbial distributions on risk estimates, at two different concentration scenarios and at a range of prevalence levels. By using five different parametric distributions, we investigate whether different characteristics of a good fit are crucial for an accurate risk estimate. Among the factors studied are the importance of accounting for the Poisson randomness in counts, the difference between treating "true" zeroes as such or as censored below a limit of quantification (LOQ) and the importance of making the correct assumption about the underlying distribution of concentrations. By running a simulation experiment with zero-inflated Poisson-lognormal distributed data and an existing QMRA model from retail to consumer level, it was possible to assess the difference between expected risk and the risk estimated with using a lognormal, a zero-inflated lognormal, a Poisson-gamma, a zero-inflated Poisson-gamma and a zero-inflated Poisson-lognormal distribution. We show that the impact of the choice of different probability distributions to describe concentrations at retail on risk estimates is dependent both on concentration and prevalence levels. We also show that the use of an LOQ should be done consciously, especially when zero-inflation is not used. In general, zero-inflation does not necessarily improve the absolute risk estimation, but performance of zero-inflated distributions in QMRA tends to be
Dodd, C.K.; Dorazio, R.M.
2004-01-01
A critical variable in both ecological and conservation field studies is determining how many individuals of a species are present within a defined sampling area. Labor intensive techniques such as capture-mark-recapture and removal sampling may provide estimates of abundance, but there are many logistical constraints to their widespread application. Many studies on terrestrial and aquatic salamanders use counts as an index of abundance, assuming that detection remains constant while sampling. If this constancy is violated, determination of detection probabilities is critical to the accurate estimation of abundance. Recently, a model was developed that provides a statistical approach that allows abundance and detection to be estimated simultaneously from spatially and temporally replicated counts. We adapted this model to estimate these parameters for salamanders sampled over a six vear period in area-constrained plots in Great Smoky Mountains National Park. Estimates of salamander abundance varied among years, but annual changes in abundance did not vary uniformly among species. Except for one species, abundance estimates were not correlated with site covariates (elevation/soil and water pH, conductivity, air and water temperature). The uncertainty in the estimates was so large as to make correlations ineffectual in predicting which covariates might influence abundance. Detection probabilities also varied among species and sometimes among years for the six species examined. We found such a high degree of variation in our counts and in estimates of detection among species, sites, and years as to cast doubt upon the appropriateness of using count data to monitor population trends using a small number of area-constrained survey plots. Still, the model provided reasonable estimates of abundance that could make it useful in estimating population size from count surveys.
Estimation of submarine mass failure probability from a sequence of deposits with age dates
Geist, Eric L.; Chaytor, Jason D.; Parsons, Thomas E.; ten Brink, Uri S.
2013-01-01
The empirical probability of submarine mass failure is quantified from a sequence of dated mass-transport deposits. Several different techniques are described to estimate the parameters for a suite of candidate probability models. The techniques, previously developed for analyzing paleoseismic data, include maximum likelihood and Type II (Bayesian) maximum likelihood methods derived from renewal process theory and Monte Carlo methods. The estimated mean return time from these methods, unlike estimates from a simple arithmetic mean of the center age dates and standard likelihood methods, includes the effects of age-dating uncertainty and of open time intervals before the first and after the last event. The likelihood techniques are evaluated using Akaike’s Information Criterion (AIC) and Akaike’s Bayesian Information Criterion (ABIC) to select the optimal model. The techniques are applied to mass transport deposits recorded in two Integrated Ocean Drilling Program (IODP) drill sites located in the Ursa Basin, northern Gulf of Mexico. Dates of the deposits were constrained by regional bio- and magnetostratigraphy from a previous study. Results of the analysis indicate that submarine mass failures in this location occur primarily according to a Poisson process in which failures are independent and return times follow an exponential distribution. However, some of the model results suggest that submarine mass failures may occur quasiperiodically at one of the sites (U1324). The suite of techniques described in this study provides quantitative probability estimates of submarine mass failure occurrence, for any number of deposits and age uncertainty distributions.
NASA Technical Reports Server (NTRS)
Courey, Karim; Wright, Clara; Asfour, Shihab; Bayliss, Jon; Ludwig, Larry
2008-01-01
Existing risk simulations make the assumption that when a free tin whisker has bridged two adjacent exposed electrical conductors, the result is an electrical short circuit. This conservative assumption is made because shorting is a random event that has a currently unknown probability associated with it. Due to contact resistance, electrical shorts may not occur at lower voltage levels. In this experiment, we study the effect of varying voltage on the breakdown of the contact resistance which leads to a short circuit. From this data, we can estimate the probability of an electrical short, as a function of voltage, given that a free tin whisker has bridged two adjacent exposed electrical conductors. In addition, three tin whiskers grown from the same Space Shuttle Orbiter card guide used in the aforementioned experiment were cross sectioned and studied using a focused ion beam (FIB).
Probability based remaining capacity estimation using data-driven and neural network model
NASA Astrophysics Data System (ADS)
Wang, Yujie; Yang, Duo; Zhang, Xu; Chen, Zonghai
2016-05-01
Since large numbers of lithium-ion batteries are composed in pack and the batteries are complex electrochemical devices, their monitoring and safety concerns are key issues for the applications of battery technology. An accurate estimation of battery remaining capacity is crucial for optimization of the vehicle control, preventing battery from over-charging and over-discharging and ensuring the safety during its service life. The remaining capacity estimation of a battery includes the estimation of state-of-charge (SOC) and state-of-energy (SOE). In this work, a probability based adaptive estimator is presented to obtain accurate and reliable estimation results for both SOC and SOE. For the SOC estimation, an n ordered RC equivalent circuit model is employed by combining an electrochemical model to obtain more accurate voltage prediction results. For the SOE estimation, a sliding window neural network model is proposed to investigate the relationship between the terminal voltage and the model inputs. To verify the accuracy and robustness of the proposed model and estimation algorithm, experiments under different dynamic operation current profiles are performed on the commercial 1665130-type lithium-ion batteries. The results illustrate that accurate and robust estimation can be obtained by the proposed method.
Recent developments on the probable maximum precipitation (PMP) estimation in China
NASA Astrophysics Data System (ADS)
Zhan, Daojiang; Zhou, Jinshang
1984-02-01
This paper deals with regional and seasonal characteristics of rain storms in China which are introducing the most intensive rainfall occurrences. The paper further summarizes the techniques and practices involved for estimating the probable maximum precipitation (PMP). In consequence of inadequate streamflow data and abundance of heavy storms in China, it would be very difficult and dubious to extrapolate a frequency curve to the long return periods required for a spillway of a major structure. Apart from this, there are often dense populated areas downstream from reservoirs. Thus, in the design criterion of earth dams and/or rockfill dams (embankment) for reservoirs of major significance and also for important small dams, whose failure could result in fatalities as well as catastrophic damages, the probable maximum precipitation and probable maximum flood should be used. Thus, generalized charts of 24-hr. point-PMP have been developed.
Estimating migratory connectivity of birds when re-encounter probabilities are heterogeneous
Cohen, Emily B.; Hostelter, Jeffrey A.; Royle, J. Andrew; Marra, Peter P.
2014-01-01
Understanding the biology and conducting effective conservation of migratory species requires an understanding of migratory connectivity – the geographic linkages of populations between stages of the annual cycle. Unfortunately, for most species, we are lacking such information. The North American Bird Banding Laboratory (BBL) houses an extensive database of marking, recaptures and recoveries, and such data could provide migratory connectivity information for many species. To date, however, few species have been analyzed for migratory connectivity largely because heterogeneous re-encounter probabilities make interpretation problematic. We accounted for regional variation in re-encounter probabilities by borrowing information across species and by using effort covariates on recapture and recovery probabilities in a multistate capture–recapture and recovery model. The effort covariates were derived from recaptures and recoveries of species within the same regions. We estimated the migratory connectivity for three tern species breeding in North America and over-wintering in the tropics, common (Sterna hirundo), roseate (Sterna dougallii), and Caspian terns (Hydroprogne caspia). For western breeding terns, model-derived estimates of migratory connectivity differed considerably from those derived directly from the proportions of re-encounters. Conversely, for eastern breeding terns, estimates were merely refined by the inclusion of re-encounter probabilities. In general, eastern breeding terns were strongly connected to eastern South America, and western breeding terns were strongly linked to the more western parts of the nonbreeding range under both models. Through simulation, we found this approach is likely useful for many species in the BBL database, although precision improved with higher re-encounter probabilities and stronger migratory connectivity. We describe an approach to deal with the inherent biases in BBL banding and re-encounter data to demonstrate
NASA Technical Reports Server (NTRS)
Courey, Karim; Wright, Clara; Asfour, Shihab; Onar, Arzu; Bayliss, Jon; Ludwig, Larry
2009-01-01
In this experiment, an empirical model to quantify the probability of occurrence of an electrical short circuit from tin whiskers as a function of voltage was developed. This empirical model can be used to improve existing risk simulation models. FIB and TEM images of a tin whisker confirm the rare polycrystalline structure on one of the three whiskers studied. FIB cross-section of the card guides verified that the tin finish was bright tin.
Time-Varying Transition Probability Matrix Estimation and Its Application to Brand Share Analysis
Chiba, Tomoaki; Akaho, Shotaro; Murata, Noboru
2017-01-01
In a product market or stock market, different products or stocks compete for the same consumers or purchasers. We propose a method to estimate the time-varying transition matrix of the product share using a multivariate time series of the product share. The method is based on the assumption that each of the observed time series of shares is a stationary distribution of the underlying Markov processes characterized by transition probability matrices. We estimate transition probability matrices for every observation under natural assumptions. We demonstrate, on a real-world dataset of the share of automobiles, that the proposed method can find intrinsic transition of shares. The resulting transition matrices reveal interesting phenomena, for example, the change in flows between TOYOTA group and GM group for the fiscal year where TOYOTA group’s sales beat GM’s sales, which is a reasonable scenario. PMID:28076383
Time-Varying Transition Probability Matrix Estimation and Its Application to Brand Share Analysis.
Chiba, Tomoaki; Hino, Hideitsu; Akaho, Shotaro; Murata, Noboru
2017-01-01
In a product market or stock market, different products or stocks compete for the same consumers or purchasers. We propose a method to estimate the time-varying transition matrix of the product share using a multivariate time series of the product share. The method is based on the assumption that each of the observed time series of shares is a stationary distribution of the underlying Markov processes characterized by transition probability matrices. We estimate transition probability matrices for every observation under natural assumptions. We demonstrate, on a real-world dataset of the share of automobiles, that the proposed method can find intrinsic transition of shares. The resulting transition matrices reveal interesting phenomena, for example, the change in flows between TOYOTA group and GM group for the fiscal year where TOYOTA group's sales beat GM's sales, which is a reasonable scenario.
How should detection probability be incorporated into estimates of relative abundance?
MacKenzie, D.I.; Kendall, W.L.
2002-01-01
Determination of the relative abundance of two populations, separated by time or space, is of interest in many ecological situations. We focus on two estimators of relative abundance, which assume that the probability that an individual is detected at least once in the survey is either equal or unequal for the two populations. We present three methods for incorporating the collected information into our inference. The first method, proposed previously, is a traditional hypothesis test for evidence that detection probabilities are unequal. However, we feel that, a priori, it is more likely that detection probabilities are actually different; hence, the burden of proof should be shifted, requiring evidence that detection probabilities are practically equivalent. The second method we present, equivalence testing, is one approach to doing so. Third, we suggest that model averaging could be used by combining the two estimators according to derived model weights. These differing approaches are applied to a mark-recapture experiment on Nuttail's cottontail rabbit (Sylvilagus nuttallii) conducted in central Oregon during 1974 and 1975, which has been previously analyzed by other authors.
[Estimation of absolute risk for fracture].
Fujiwara, Saeko
2009-03-01
Osteoporosis treatment aims to prevent fractures and maintain the QOL of the elderly. However, persons at high risk of future fracture cannot be effectively identified on the basis of bone density (BMD) alone, although BMD is used as an diagnostic criterion. Therefore, the WHO recommended that absolute risk for fracture (10-year probability of fracture) for each individual be evaluated and used as an index for intervention threshold. The 10-year probability of fracture is calculated based on age, sex, BMD at the femoral neck (body mass index if BMD is not available), history of previous fractures, parental hip fracture history, smoking, steroid use, rheumatoid arthritis, secondary osteoporosis and alcohol consumption. The WHO has just announced the development of a calculation tool (FRAX: WHO Fracture Risk Assessment Tool) in February this year. Fractures could be prevented more effectively if, based on each country's medical circumstances, an absolute risk value for fracture to determine when to start medical treatment is established and persons at high risk of fracture are identified and treated accordingly.
[Estimation of risk areas for hepatitis A].
Braga, Ricardo Cerqueira Campos; Valencia, Luís Iván Ortiz; Medronho, Roberto de Andrade; Escosteguy, Claudia Caminha
2008-08-01
This study estimated hepatitis A risk areas in a region of Duque de Caxias, Rio de Janeiro State, Brazil. A cross-sectional study consisting of a hepatitis A serological survey and a household survey were conducted in 19 census tracts. Of these, 11 tracts were selected and 1,298 children from one to ten years of age were included in the study. Geostatistical techniques allowed modeling the spatial continuity of hepatitis A, non-use of filtered drinking water, time since installation of running water, and number of water taps per household and their spatial estimation through ordinary and indicator kriging. Adjusted models for the outcome and socioeconomic variables were isotropic; risk maps were constructed; cross-validation of the four models was satisfactory. Spatial estimation using the kriging method detected areas with increased risk of hepatitis A, independently of the urban administrative area in which the census tracts were located.
PIGS: improved estimates of identity-by-descent probabilities by probabilistic IBD graph sampling.
Park, Danny S; Baran, Yael; Hormozdiari, Farhad; Eng, Celeste; Torgerson, Dara G; Burchard, Esteban G; Zaitlen, Noah
2015-01-01
Identifying segments in the genome of different individuals that are identical-by-descent (IBD) is a fundamental element of genetics. IBD data is used for numerous applications including demographic inference, heritability estimation, and mapping disease loci. Simultaneous detection of IBD over multiple haplotypes has proven to be computationally difficult. To overcome this, many state of the art methods estimate the probability of IBD between each pair of haplotypes separately. While computationally efficient, these methods fail to leverage the clique structure of IBD resulting in less powerful IBD identification, especially for small IBD segments.
a Parametric Study of Eddy Current Response for Probability of Detection Estimation
NASA Astrophysics Data System (ADS)
Hoppe, W. C.
2010-02-01
In the study reported here, historical Probability of Detection (POD) data for eddy current inspections were analyzed using an extension of the "a-hat versus a" model in order to better account for known crack variables and thereby better separate system and crack factors influencing the POD parameters. Intriguing insights have been gained in the process suggesting a simple model for POD estimation. The parametric model will be presented including results of the study and suggestions for further research.
1980-03-01
H. Phelps, Stanley M. Halpin, Edgar M. Johnson, and Franklin L. Moses HUMAN FACTORS TECHNICAL AREA U. S. Army Research Institute for the Behavioral...Army Technical Director Commander NOTICES DISTRIBUTION: Primatry distribution of this rewot ha been mode by ARI. PIS.. addrescorrespondence 0O~rniflll...explored by relating the psychological research on the use of subjective probability estimates with the need of Army intelli- gence analysts to
NASA Technical Reports Server (NTRS)
Courey, Karim J.; Asfour, Shihab S.; Onar, Arzu; Bayliss, Jon A.; Ludwig, Larry L.; Wright, Maria C.
2009-01-01
To comply with lead-free legislation, many manufacturers have converted from tin-lead to pure tin finishes of electronic components. However, pure tin finishes have a greater propensity to grow tin whiskers than tin-lead finishes. Since tin whiskers present an electrical short circuit hazard in electronic components, simulations have been developed to quantify the risk of said short circuits occurring. Existing risk simulations make the assumption that when a free tin whisker has bridged two adjacent exposed electrical conductors, the result is an electrical short circuit. This conservative assumption is made because shorting is a random event that had an unknown probability associated with it. Note however that due to contact resistance electrical shorts may not occur at lower voltage levels. In our first article we developed an empirical probability model for tin whisker shorting. In this paper, we develop a more comprehensive empirical model using a refined experiment with a larger sample size, in which we studied the effect of varying voltage on the breakdown of the contact resistance which leads to a short circuit. From the resulting data we estimated the probability distribution of an electrical short, as a function of voltage. In addition, the unexpected polycrystalline structure seen in the focused ion beam (FIB) cross section in the first experiment was confirmed in this experiment using transmission electron microscopy (TEM). The FIB was also used to cross section two card guides to facilitate the measurement of the grain size of each card guide's tin plating to determine its finish.
A robust design mark-resight abundance estimator allowing heterogeneity in resighting probabilities
McClintock, B.T.; White, Gary C.; Burnham, K.P.
2006-01-01
This article introduces the beta-binomial estimator (BBE), a closed-population abundance mark-resight model combining the favorable qualities of maximum likelihood theory and the allowance of individual heterogeneity in sighting probability (p). The model may be parameterized for a robust sampling design consisting of multiple primary sampling occasions where closure need not be met between primary occasions. We applied the model to brown bear data from three study areas in Alaska and compared its performance to the joint hypergeometric estimator (JHE) and Bowden's estimator (BOWE). BBE estimates suggest heterogeneity levels were non-negligible and discourage the use of JHE for these data. Compared to JHE and BOWE, confidence intervals were considerably shorter for the AICc model-averaged BBE. To evaluate the properties of BBE relative to JHE and BOWE when sample sizes are small, simulations were performed with data from three primary occasions generated under both individual heterogeneity and temporal variation in p. All models remained consistent regardless of levels of variation in p. In terms of precision, the AICc model-averaged BBE showed advantages over JHE and BOWE when heterogeneity was present and mean sighting probabilities were similar between primary occasions. Based on the conditions examined, BBE is a reliable alternative to JHE or BOWE and provides a framework for further advances in mark-resight abundance estimation. ?? 2006 American Statistical Association and the International Biometric Society.
Maximum a posteriori probability estimation for localizing damage using ultrasonic guided waves
NASA Astrophysics Data System (ADS)
Flynn, Eric B.; Todd, Michael D.; Wilcox, Paul D.; Drinkwater, Bruce W.; Croxford, Anthony J.
2011-04-01
Presented is an approach to damage localization for guided wave structural health monitoring (GWSHM) in plate-like structures. In this mode of SHM, transducers excite and sense guided waves in order to detect and characterize the presence of damage. The premise of the presented localization approach is simple: use as the estimated damage location the point on the structure with the maximum a posteriori probability (MAP) of being the location of damage (i.e., the most probable location given a set of sensor measurements). This is accomplished by constructing a minimally-informed statistical model of the GWSHM process. Parameters of the model which are unknown, such as scattered wave amplitude, are assigned non-informative Bayesian prior distributions and averaged out of the a posteriori probability calculation. Using an ensemble of measurements from an instrumented plate with stiffening stringers, the performance of the MAP estimate is compared to that of what were found to be the two most effective previously reported algorithms. The MAP estimate proved superior in nearly all test cases and was particularly effective in localizing damage using very sparse arrays of as few as three transducers.
Kendall, W.L.; Nichols, J.D.
2002-01-01
Temporary emigration was identified some time ago as causing potential problems in capture-recapture studies, and in the last five years approaches have been developed for dealing with special cases of this general problem. Temporary emigration can be viewed more generally as involving transitions to and from an unobservable state, and frequently the state itself is one of biological interest (e.g., 'nonbreeder'). Development of models that permit estimation of relevant parameters in the presence of an unobservable state requires either extra information (e.g., as supplied by Pollock's robust design) or the following classes of model constraints: reducing the order of Markovian transition probabilities, imposing a degree of determinism on transition probabilities, removing state specificity of survival probabilities, and imposing temporal constancy of parameters. The objective of the work described in this paper is to investigate estimability of model parameters under a variety of models that include an unobservable state. Beginning with a very general model and no extra information, we used numerical methods to systematically investigate the use of ancillary information and constraints to yield models that are useful for estimation. The result is a catalog of models for which estimation is possible. An example analysis of sea turtle capture-recapture data under two different models showed similar point estimates but increased precision for the model that incorporated ancillary data (the robust design) when compared to the model with deterministic transitions only. This comparison and the results of our numerical investigation of model structures lead to design suggestions for capture-recapture studies in the presence of an unobservable state.
NASA Astrophysics Data System (ADS)
Barengoltz, Jack
2016-07-01
Monte Carlo (MC) is a common method to estimate probability, effectively by a simulation. For planetary protection, it may be used to estimate the probability of impact P{}_{I} by a launch vehicle (upper stage) of a protected planet. The object of the analysis is to provide a value for P{}_{I} with a given level of confidence (LOC) that the true value does not exceed the maximum allowed value of P{}_{I}. In order to determine the number of MC histories required, one must also guess the maximum number of hits that will occur in the analysis. This extra parameter is needed because a LOC is desired. If more hits occur, the MC analysis would indicate that the true value may exceed the specification value with a higher probability than the LOC. (In the worst case, even the mean value of the estimated P{}_{I} might exceed the specification value.) After the analysis is conducted, the actual number of hits is, of course, the mean. The number of hits arises from a small probability per history and a large number of histories; these are the classic requirements for a Poisson distribution. For a known Poisson distribution (the mean is the only parameter), the probability for some interval in the number of hits is calculable. Before the analysis, this is not possible. Fortunately, there are methods that can bound the unknown mean for a Poisson distribution. F. Garwoodfootnote{ F. Garwood (1936), ``Fiduciary limits for the Poisson distribution.'' Biometrika 28, 437-442.} published an appropriate method that uses the Chi-squared function, actually its inversefootnote{ The integral chi-squared function would yield probability α as a function of the mean µ and an actual value n.} (despite the notation used): This formula for the upper and lower limits of the mean μ with the two-tailed probability 1-α depends on the LOC α and an estimated value of the number of "successes" n. In a MC analysis for planetary protection, only the upper limit is of interest, i.e., the single
Greenberg, Joshua; Price, Bertram; Ware, Adam
2010-04-01
Microbial source tracking (MST) is a procedure used to determine the relative contributions of humans and animals to fecal microbial contamination of surface waters in a given watershed. Studies of MST methodology have focused on optimizing sampling, laboratory, and statistical analysis methods in order to improve the reliability of determining which sources contributed most to surface water fecal contaminant. The usual approach for estimating a source distribution of microbial contamination is to classify water sample microbial isolates into discrete source categories and calculate the proportion of these isolates in each source category. The set of proportions is an estimate of the contaminant source distribution. In this paper we propose and compare an alternative method for estimating a source distribution-averaging posterior probabilities of source identity across isolates. We conducted a Monte Carlo simulation covering a wide variety of watershed scenarios to compare the two methods. The results show that averaging source posterior probabilities across isolates leads to more accurate source distribution estimates than proportions that follow classification.
Spatial ascariasis risk estimation using socioeconomic variables.
Valencia, Luis Iván Ortiz; Fortes, Bruno de Paula Menezes Drumond; Medronho, Roberto de Andrade
2005-12-01
Frequently, disease incidence is mapped as area data, for example, census tracts, districts or states. Spatial disease incidence can be highly heterogeneous inside these areas. Ascariasis is a highly prevalent disease, which is associated with poor sanitation and hygiene. Geostatistics was applied to model spatial distribution of Ascariasis risk and socioeconomic risk events in a poor community in Rio de Janeiro, Brazil. Data were gathered from a coproparasitologic and a domiciliary survey in 1550 children aged 1-9. Ascariasis risk and socioeconomic risk events were spatially estimated using Indicator Kriging. Cokriging models with a Linear Model of Coregionalization incorporating one socioeconomic variable were implemented. If a housewife attended school for less than four years, the non-use of a home water filter, a household density greater than one, and a household income lower than one Brazilian minimum wage increased the risk of Ascariasis. Cokriging improved spatial estimation of Ascariasis risk areas when compared to Indicator Kriging and detected more Ascariasis very-high risk areas than the GIS Overlay method.
Estimates of EPSP amplitude based on changes in motoneuron discharge rate and probability.
Powers, Randall K; Türker, K S
2010-10-01
When motor units are discharging tonically, transient excitatory synaptic inputs produce an increase in the probability of spike occurrence and also increase the instantaneous discharge rate. Several researchers have proposed that these induced changes in discharge rate and probability can be used to estimate the amplitude of the underlying excitatory post-synaptic potential (EPSP). We tested two different methods of estimating EPSP amplitude by comparing the amplitude of simulated EPSPs with their effects on the discharge of rat hypoglossal motoneurons recorded in an in vitro brainstem slice preparation. The first estimation method (simplified-trajectory method) is based on the assumptions that the membrane potential trajectory between spikes can be approximated by a 10 mV post-spike hyperpolarization followed by a linear rise to the next spike and that EPSPs sum linearly with this trajectory. We hypothesized that this estimation method would not be accurate due to interspike variations in membrane conductance and firing threshold that are not included in the model and that an alternative method based on estimating the effective distance to threshold would provide more accurate estimates of EPSP amplitude. This second method (distance-to-threshold method) uses interspike interval statistics to estimate the effective distance to threshold throughout the interspike interval and incorporates this distance-to-threshold trajectory into a threshold-crossing model. We found that the first method systematically overestimated the amplitude of small (<5 mV) EPSPs and underestimated the amplitude of large (>5 mV EPSPs). For large EPSPs, the degree of underestimation increased with increasing background discharge rate. Estimates based on the second method were more accurate for small EPSPs than those based on the first model, but estimation errors were still large for large EPSPs. These errors were likely due to two factors: (1) the distance to threshold can only be
NASA Technical Reports Server (NTRS)
Edmonds, L. D.
2016-01-01
Since advancing technology has been producing smaller structures in electronic circuits, the floating gates in modern flash memories are becoming susceptible to prompt charge loss from ionizing radiation environments found in space. A method for estimating the risk of a charge-loss event is given.
NASA Technical Reports Server (NTRS)
Edmonds, L. D.
2016-01-01
Because advancing technology has been producing smaller structures in electronic circuits, the floating gates in modern flash memories are becoming susceptible to prompt charge loss from ionizing radiation environments found in space. A method for estimating the risk of a charge-loss event is given.
NASA Astrophysics Data System (ADS)
Eleftheriadou, Anastasia K.; Baltzopoulou, Aikaterini D.; Karabinis, Athanasios I.
2016-06-01
The current seismic risk assessment is based on two discrete approaches, actual and probable, validating afterwards the produced results. In the first part of this research, the seismic risk is evaluated from the available data regarding the mean statistical repair/strengthening or replacement cost for the total number of damaged structures (180,427 buildings) after the 7/9/1999 Parnitha (Athens) earthquake. The actual evaluated seismic risk is afterwards compared to the estimated probable structural losses, which is presented in the second part of the paper, based on a damage scenario in the referring earthquake. The applied damage scenario is based on recently developed damage probability matrices (DPMs) from Athens (Greece) damage database. The seismic risk estimation refers to 750,085 buildings situated in the extended urban region of Athens. The building exposure is categorized in five typical structural types and represents 18.80 % of the entire building stock in Greece. The last information is provided by the National Statistics Service of Greece (NSSG) according to the 2000-2001 census. The seismic input is characterized by the ratio, a g/ a o, where a g is the regional peak ground acceleration (PGA) which is evaluated from the earlier estimated research macroseismic intensities, and a o is the PGA according to the hazard map of the 2003 Greek Seismic Code. Finally, the collected investigated financial data derived from different National Services responsible for the post-earthquake crisis management concerning the repair/strengthening or replacement costs or other categories of costs for the rehabilitation of earthquake victims (construction and function of settlements for earthquake homeless, rent supports, demolitions, shorings) are used to determine the final total seismic risk factor.
Saarela, Olli; Liu, Zhihui Amy
2016-10-15
Marginal structural Cox models are used for quantifying marginal treatment effects on outcome event hazard function. Such models are estimated using inverse probability of treatment and censoring (IPTC) weighting, which properly accounts for the impact of time-dependent confounders, avoiding conditioning on factors on the causal pathway. To estimate the IPTC weights, the treatment assignment mechanism is conventionally modeled in discrete time. While this is natural in situations where treatment information is recorded at scheduled follow-up visits, in other contexts, the events specifying the treatment history can be modeled in continuous time using the tools of event history analysis. This is particularly the case for treatment procedures, such as surgeries. In this paper, we propose a novel approach for flexible parametric estimation of continuous-time IPTC weights and illustrate it in assessing the relationship between metastasectomy and mortality in metastatic renal cell carcinoma patients. Copyright © 2016 John Wiley & Sons, Ltd.
Estimation of probable maximum precipitation for catchments in eastern India by a generalized method
NASA Astrophysics Data System (ADS)
Rakhecha, P. R.; Mandal, B. N.; Kulkarni, A. K.; Deshpande, N. R.
1995-03-01
A generalized method to estimate the probable maximum precipitation (PMP) has been developed for catchments in eastern India (80° E, 18° N) by pooling together all the major rainstorms that have occurred in this area. The areal raindepths of these storms are normalized for factors such as storm dew point temperature, distance of the storm from the coast, topographic effects and any intervening mountain barriers between the storm area and the moisture source. The normalized values are then applied, with appropriate adjustment factors in estimating PMP raindepths, to the Subarnarekha river catchment (upto the Chandil dam site) with an area of 5663 km2. The PMP rainfall for 1, 2 and 3 days were found to be roughly 53 cm, 78 cm and 98 cm, respectively. It is expected that the application of the generalized method proposed here will give more reliable estimates of PMP for different duration rainfall events.
McGinn, Thomas; Jervis, Ramiro; Wisnivesky, Juan; Keitz, Sheri
2008-01-01
Background Clinical prediction rules (CPR) are tools that clinicians can use to predict the most likely diagnosis, prognosis, or response to treatment in a patient based on individual characteristics. CPRs attempt to standardize, simplify, and increase the accuracy of clinicians’ diagnostic and prognostic assessments. The teaching tips series is designed to give teachers advice and materials they can use to attain specific educational objectives. Educational Objectives In this article, we present 3 teaching tips aimed at helping clinical learners use clinical prediction rules and to more accurately assess pretest probability in every day practice. The first tip is designed to demonstrate variability in physician estimation of pretest probability. The second tip demonstrates how the estimate of pretest probability influences the interpretation of diagnostic tests and patient management. The third tip exposes learners to various examples and different types of Clinical Prediction Rules (CPR) and how to apply them in practice. Pilot Testing We field tested all 3 tips with 16 learners, a mix of interns and senior residents. Teacher preparatory time was approximately 2 hours. The field test utilized a board and a data projector; 3 handouts were prepared. The tips were felt to be clear and the educational objectives reached. Potential teaching pitfalls were identified. Conclusion Teaching with these tips will help physicians appreciate the importance of applying evidence to their every day decisions. In 2 or 3 short teaching sessions, clinicians can also become familiar with the use of CPRs in applying evidence consistently in everyday practice. PMID:18491194
A generalised technique for the estimation of probable maximum precipitation in India
NASA Astrophysics Data System (ADS)
Rakhecha, P. R.; Kennedy, M. R.
1985-06-01
In this paper a version of a generalised method of estimating probable maximum precipitation (PMP) is applied to the catchments of four large dams in India. The value of a secure dam is high both in terms of human life and in economic terms. Reliable estimates of PMP are required in estimating the design flood for spillways of large earth and rockfill dams. Estimates of PMP obtained using the traditional method of moisture maximisation and storm transposition can be unreliable as highly efficient rain storms may not be represented in the rainfall records of an area. Generalised methods of (calculating) PMP are used to obtain reliable estimates of PMP and also to give estimates which are consistent over a region. This is done by pooling together all the rainfall data from a very large area. The rainfall depths are normalised for such factors as storm dew-point temperature, distance of the storm from the coast, topographic effects and any intervening mountain barriers between the rainfall area and the moisture source. These normalised values can then be applied to any individual catchment, with the appropriate adjustment factors.
Geissler, P.H.; Moyer, L.M.
1983-01-01
Four sampling and estimation methods for estimating the number of red-cockaded woodpecker colonies on National Forests in the Southeast were compared, using samples chosen from simulated populations based on the observed sample. The methods included (1) simple random sampling without replacement using a mean per sampling unit estimator, (2) simple random sampling without replacement with a ratio per pine area estimator, (3) probability proportional to 'size' sampling with replacement, and (4) probability proportional to 'size' without replacement using Murthy's estimator. The survey sample of 274 National Forest compartments (1000 acres each) constituted a superpopulation from which simulated stratum populations were selected with probability inversely proportional to the original probability of selection. Compartments were originally sampled with probabilities proportional to the probabilities that the compartments contained woodpeckers ('size'). These probabilities were estimated with a discriminant analysis based on tree species and tree age. The ratio estimator would have been the best estimator for this survey based on the mean square error. However, if more accurate predictions of woodpecker presence had been available, Murthy's estimator would have been the best. A subroutine to calculate Murthy's estimates is included; it is computationally feasible to analyze up to 10 samples per stratum.
Estimates of health risk from exposure to radioactive pollutants
Sullivan, R.E.; Nelson, N.S.; Ellett, W.H.; Dunning, D.E. Jr.; Leggett, R.W.; Yalcintas, M.G.; Eckerman, K.F.
1981-11-01
A dosimetric and health effects analysis has been performed for the Office of Radiation Programs of the Environmental Protection Agency (EPA) to assess potential hazards from radioactive pollutants. Contemporary dosimetric methods were used to obtain estimates of dose rates to reference organs from internal exposures due to either inhalation of contaminated air or ingestion of contaminated food, or from external exposures due to either immersion in contaminated air or proximity to contaminated ground surfaces. These dose rates were then used to estimate the number of premature cancer deaths arising from such exposures and the corresponding number of years of life lost in a cohort of 100,000 persons, all simultaneously liveborn and all going through life with the same risks of dying from competing causes. The risk of dying from a competing cause for a given year was taken to be the probability of dying from all causes as given in a recent actuarial life table for the total US population.
A predictive model to estimate the pretest probability of metastasis in patients with osteosarcoma.
Wang, Sisheng; Zheng, Shaoluan; Hu, Kongzu; Sun, Heyan; Zhang, Jinling; Rong, Genxiang; Gao, Jie; Ding, Nan; Gui, Binjie
2017-01-01
Osteosarcomas (OSs) represent a huge challenge to improve the overall survival, especially in metastatic patients. Increasing evidence indicates that both tumor-associated elements but also on host-associated elements are under a remarkable effect on the prognosis of cancer patients, especially systemic inflammatory response. By analyzing a series prognosis of factors, including age, gender, primary tumor size, tumor location, tumor grade, and histological classification, monocyte ratio, and NLR ratio, a clinical predictive model was established by using stepwise logistic regression involved circulating leukocyte to compute the estimated probabilities of metastases for OS patients. The clinical predictive model was described by the following equations: probability of developing metastases = ex/(1 + ex), x = -2.150 + (1.680 × monocyte ratio) + (1.533 × NLR ratio), where is the base of the natural logarithm, the assignment to each of the 2 variables is 1 if the ratio >1 (otherwise 0). The calculated AUC of the receiver-operating characteristic curve as 0.793 revealed well accuracy of this model (95% CI, 0.740-0.845). The predicted probabilities that we generated with the cross-validation procedure had a similar AUC (0.743; 95% CI, 0.684-0.803). The present model could be used to improve the outcomes of the metastases by developing a predictive model considering circulating leukocyte influence to estimate the pretest probability of developing metastases in patients with OS.
A predictive model to estimate the pretest probability of metastasis in patients with osteosarcoma
Wang, Sisheng; Zheng, Shaoluan; Hu, Kongzu; Sun, Heyan; Zhang, Jinling; Rong, Genxiang; Gao, Jie; Ding, Nan; Gui, Binjie
2017-01-01
Abstract Osteosarcomas (OSs) represent a huge challenge to improve the overall survival, especially in metastatic patients. Increasing evidence indicates that both tumor-associated elements but also on host-associated elements are under a remarkable effect on the prognosis of cancer patients, especially systemic inflammatory response. By analyzing a series prognosis of factors, including age, gender, primary tumor size, tumor location, tumor grade, and histological classification, monocyte ratio, and NLR ratio, a clinical predictive model was established by using stepwise logistic regression involved circulating leukocyte to compute the estimated probabilities of metastases for OS patients. The clinical predictive model was described by the following equations: probability of developing metastases = ex/(1 + ex), x = −2.150 + (1.680 × monocyte ratio) + (1.533 × NLR ratio), where is the base of the natural logarithm, the assignment to each of the 2 variables is 1 if the ratio >1 (otherwise 0). The calculated AUC of the receiver-operating characteristic curve as 0.793 revealed well accuracy of this model (95% CI, 0.740–0.845). The predicted probabilities that we generated with the cross-validation procedure had a similar AUC (0.743; 95% CI, 0.684–0.803). The present model could be used to improve the outcomes of the metastases by developing a predictive model considering circulating leukocyte influence to estimate the pretest probability of developing metastases in patients with OS. PMID:28099353
Estimating survival and breeding probability for pond-breeding amphibians: a modified robust design
Bailey, L.L.; Kendall, W.L.; Church, D.R.; Wilbur, H.M.
2004-01-01
Many studies of pond-breeding amphibians involve sampling individuals during migration to and from breeding habitats. Interpreting population processes and dynamics from these studies is difficult because (1) only a proportion of the population is observable each season, while an unknown proportion remains unobservable (e.g., non-breeding adults) and (2) not all observable animals are captured. Imperfect capture probability can be easily accommodated in capture?recapture models, but temporary transitions between observable and unobservable states, often referred to as temporary emigration, is known to cause problems in both open- and closed-population models. We develop a multistate mark?recapture (MSMR) model, using an open-robust design that permits one entry and one exit from the study area per season. Our method extends previous temporary emigration models (MSMR with an unobservable state) in two ways. First, we relax the assumption of demographic closure (no mortality) between consecutive (secondary) samples, allowing estimation of within-pond survival. Also, we add the flexibility to express survival probability of unobservable individuals (e.g., ?non-breeders?) as a function of the survival probability of observable animals while in the same, terrestrial habitat. This allows for potentially different annual survival probabilities for observable and unobservable animals. We apply our model to a relictual population of eastern tiger salamanders (Ambystoma tigrinum tigrinum). Despite small sample sizes, demographic parameters were estimated with reasonable precision. We tested several a priori biological hypotheses and found evidence for seasonal differences in pond survival. Our methods could be applied to a variety of pond-breeding species and other taxa where individuals are captured entering or exiting a common area (e.g., spawning or roosting area, hibernacula).
Lamb, Jennifer Y.; Waddle, J. Hardin; Qualls, Carl P.
2017-01-01
Large gaps exist in our knowledge of the ecology of stream-breeding plethodontid salamanders in the Gulf Coastal Plain. Data describing where these salamanders are likely to occur along environmental gradients, as well as their likelihood of detection, are important for the prevention and management of amphibian declines. We used presence/absence data from leaf litter bag surveys and a hierarchical Bayesian multispecies single-season occupancy model to estimate the occurrence of five species of plethodontids across reaches in headwater streams in the Gulf Coastal Plain. Average detection probabilities were high (range = 0.432–0.942) and unaffected by sampling covariates specific to the use of litter bags (i.e., bag submergence, sampling season, in-stream cover). Estimates of occurrence probabilities differed substantially between species (range = 0.092–0.703) and were influenced by the size of the upstream drainage area and by the maximum proportion of the reach that dried. The effects of these two factors were not equivalent across species. Our results demonstrate that hierarchical multispecies models successfully estimate occurrence parameters for both rare and common stream-breeding plethodontids. The resulting models clarify how species are distributed within stream networks, and they provide baseline values that will be useful in evaluating the conservation statuses of plethodontid species within lotic systems in the Gulf Coastal Plain.
Estimating superpopulation size and annual probability of breeding for pond-breeding salamanders
Kinkead, K.E.; Otis, D.L.
2007-01-01
It has long been accepted that amphibians can skip breeding in any given year, and environmental conditions act as a cue for breeding. In this paper, we quantify temporary emigration or nonbreeding probability for mole and spotted salamanders (Ambystoma talpoideum and A. maculatum). We estimated that 70% of mole salamanders may skip breeding during an average rainfall year and 90% may skip during a drought year. Spotted salamanders may be more likely to breed, with only 17% avoiding the breeding pond during an average rainfall year. We illustrate how superpopulations can be estimated using temporary emigration probability estimates. The superpopulation is the total number of salamanders associated with a given breeding pond. Although most salamanders stay within a certain distance of a breeding pond for the majority of their life spans, it is difficult to determine true overall population sizes for a given site if animals are only captured during a brief time frame each year with some animals unavailable for capture at any time during a given year. ?? 2007 by The Herpetologists' League, Inc.
Modeling and estimation of stage-specific daily survival probabilities of nests
Stanley, T.R.
2000-01-01
In studies of avian nesting success, it is often of interest to estimate stage-specific daily survival probabilities of nests. When data can be partitioned by nesting stage (e.g., incubation stage, nestling stage), piecewise application of the Mayfield method or Johnsona??s method is appropriate. However, when the data contain nests where the transition from one stage to the next occurred during the interval between visits, piecewise approaches are inappropriate. In this paper, I present a model that allows joint estimation of stage-specific daily survival probabilities even when the time of transition between stages is unknown. The model allows interval lengths between visits to nests to vary, and the exact time of failure of nests does not need to be known. The performance of the model at various sample sizes and interval lengths between visits was investigated using Monte Carlo simulations, and it was found that the model performed quite well: bias was small and confidence-interval coverage was at the nominal 95% rate. A SAS program for obtaining maximum likelihood estimates of parameters, and their standard errors, is provided in the Appendix.
Olson, Scott A.; Brouillette, Michael C.
2006-01-01
A logistic regression equation was developed for estimating the probability of a stream flowing intermittently at unregulated, rural stream sites in Vermont. These determinations can be used for a wide variety of regulatory and planning efforts at the Federal, State, regional, county and town levels, including such applications as assessing fish and wildlife habitats, wetlands classifications, recreational opportunities, water-supply potential, waste-assimilation capacities, and sediment transport. The equation will be used to create a derived product for the Vermont Hydrography Dataset having the streamflow characteristic of 'intermittent' or 'perennial.' The Vermont Hydrography Dataset is Vermont's implementation of the National Hydrography Dataset and was created at a scale of 1:5,000 based on statewide digital orthophotos. The equation was developed by relating field-verified perennial or intermittent status of a stream site during normal summer low-streamflow conditions in the summer of 2005 to selected basin characteristics of naturally flowing streams in Vermont. The database used to develop the equation included 682 stream sites with drainage areas ranging from 0.05 to 5.0 square miles. When the 682 sites were observed, 126 were intermittent (had no flow at the time of the observation) and 556 were perennial (had flowing water at the time of the observation). The results of the logistic regression analysis indicate that the probability of a stream having intermittent flow in Vermont is a function of drainage area, elevation of the site, the ratio of basin relief to basin perimeter, and the areal percentage of well- and moderately well-drained soils in the basin. Using a probability cutpoint (a lower probability indicates the site has perennial flow and a higher probability indicates the site has intermittent flow) of 0.5, the logistic regression equation correctly predicted the perennial or intermittent status of 116 test sites 85 percent of the time.
Estimated probability of arsenic in groundwater from bedrock aquifers in New Hampshire, 2011
Ayotte, Joseph D.; Cahillane, Matthew; Hayes, Laura; Robinson, Keith W.
2012-01-01
The statewide maps generated by the probability models are not designed to predict arsenic concentration in any single well, but they are expected to provide useful information in areas of the State that currently contain little to no data on arsenic concentration. They also may aid in resource decision making, in determining potential risk for private wells, and in ecological-level analysis of disease outcomes. The approach for modeling arsenic in groundwater could also be applied to other environmental contaminants that have potential implications for human health, such as uranium, radon, fluoride, manganese, volatile organic compounds, nitrate, and bacteria.
Lukeš, Tomáš; Křížek, Pavel; Švindrych, Zdeněk; Benda, Jakub; Ovesný, Martin; Fliegel, Karel; Klíma, Miloš; Hagen, Guy M
2014-12-01
We introduce and demonstrate a new high performance image reconstruction method for super-resolution structured illumination microscopy based on maximum a posteriori probability estimation (MAP-SIM). Imaging performance is demonstrated on a variety of fluorescent samples of different thickness, labeling density and noise levels. The method provides good suppression of out of focus light, improves spatial resolution, and allows reconstruction of both 2D and 3D images of cells even in the case of weak signals. The method can be used to process both optical sectioning and super-resolution structured illumination microscopy data to create high quality super-resolution images.
Local neighborhood transition probability estimation and its use in contextual classification
NASA Technical Reports Server (NTRS)
Chittineni, C. B.
1979-01-01
The problem of incorporating spatial or contextual information into classifications is considered. A simple model that describes the spatial dependencies between the neighboring pixels with a single parameter, Theta, is presented. Expressions are derived for updating the posteriori probabilities of the states of nature of the pattern under consideration using information from the neighboring patterns, both for spatially uniform context and for Markov dependencies in terms of Theta. Techniques for obtaining the optimal value of the parameter Theta as a maximum likelihood estimate from the local neighborhood of the pattern under consideration are developed.
Estimating the probability of allelic drop-out of STR alleles in forensic genetics.
Tvedebrink, Torben; Eriksen, Poul Svante; Mogensen, Helle Smidt; Morling, Niels
2009-09-01
In crime cases with available DNA evidence, the amount of DNA is often sparse due to the setting of the crime. In such cases, allelic drop-out of one or more true alleles in STR typing is possible. We present a statistical model for estimating the per locus and overall probability of allelic drop-out using the results of all STR loci in the case sample as reference. The methodology of logistic regression is appropriate for this analysis, and we demonstrate how to incorporate this in a forensic genetic framework.
Southern California regional earthquake probability estimated from continuous GPS geodetic data
NASA Astrophysics Data System (ADS)
Anderson, G.
2002-12-01
Current seismic hazard estimates are primarily based on seismic and geologic data, but geodetic measurements from large, dense arrays such as the Southern California Integrated GPS Network (SCIGN) can also be used to estimate earthquake probabilities and seismic hazard. Geodetically-derived earthquake probability estimates are particularly important in regions with poorly-constrained fault slip rates. In addition, they are useful because such estimates come with well-determined error bounds. Long-term planning is underway to incorporate geodetic data in the next generation of United States national seismic hazard maps, and techniques for doing so need further development. I present a new method for estimating the expected rates of earthquakes using strain rates derived from geodetic station velocities. I compute the strain rates using a new technique devised by Y. Hsu and M. Simons [Y. Hsu and M. Simons, pers. comm.], which computes the horizontal strain rate tensor ( {˙ {ɛ}}) at each node of a pre-defined regular grid, using all geodetic velocities in the data set weighted by distance and estimated uncertainty. In addition, they use a novel weighting to handle the effects of station distribution: they divide the region covered by the geodetic network into Voronoi cells using the station locations and weight each station's contribution to {˙ {ɛ}} by the area of the Voronoi cell centered at that station. I convert {˙ {ɛ}} into the equivalent seismic moment rate density (˙ {M}) using the method of \\textit{Savage and Simpson} [1997] and maximum seismogenic depths estimated from regional seismicity; ˙ {M} gives the expected rate of seismic moment release in a region, based on the geodetic strain rates. Assuming the seismicity in the given region follows a Gutenberg-Richter relationship, I convert ˙ {M} to an expected rate of earthquakes of a given magnitude. I will present results of a study applying this method to data from the SCIGN array to estimate
Estimated Autism Risk and Older Reproductive Age
King, Marissa D.; Fountain, Christine; Dakhlallah, Diana
2009-01-01
Objectives. We sought to estimate the risk for autism associated with maternal and paternal age across successive birth cohorts. Methods. We linked birth records and autism diagnostic records from the California Department of Developmental Services for children born in California between 1992 and 2000 to calculate the risk associated with maternal and paternal age for each birth cohort as well as for the pooled data. Results. The categorical risks associated with maternal age over 40 years ranged from a high of 1.84 (95% confidence interval [CI] = 1.37, 2.47) to a low of 1.27 (95% CI = 0.95, 1.69). The risk associated with paternal age ranged from 1.29 (95% CI = 1.03, 1.6) to 1.71 (95% CI = 1.41, 2.08). Conclusions. Pooling data across multiple birth cohorts inflates the risk associated with paternal age. Analyses that do not suffer from problems produced by pooling across birth cohorts demonstrated that advanced maternal age, rather than paternal age, may pose greater risk. Future research examining parental age as a risk factor must be careful to avoid the paradoxes that can arise from pooling data, particularly during periods of social demographic change. PMID:19608957
Risk Estimation Methodology for Launch Accidents.
Clayton, Daniel James; Lipinski, Ronald J.; Bechtel, Ryan D.
2014-02-01
As compact and light weight power sources with reliable, long lives, Radioisotope Power Systems (RPSs) have made space missions to explore the solar system possible. Due to the hazardous material that can be released during a launch accident, the potential health risk of an accident must be quantified, so that appropriate launch approval decisions can be made. One part of the risk estimation involves modeling the response of the RPS to potential accident environments. Due to the complexity of modeling the full RPS response deterministically on dynamic variables, the evaluation is performed in a stochastic manner with a Monte Carlo simulation. The potential consequences can be determined by modeling the transport of the hazardous material in the environment and in human biological pathways. The consequence analysis results are summed and weighted by appropriate likelihood values to give a collection of probabilistic results for the estimation of the potential health risk. This information is used to guide RPS designs, spacecraft designs, mission architecture, or launch procedures to potentially reduce the risk, as well as to inform decision makers of the potential health risks resulting from the use of RPSs for space missions.
NASA Astrophysics Data System (ADS)
Ascasibar, Yago
2010-08-01
The Field Estimator for Arbitrary Spaces (FiEstAS) computes the continuous probability density field underlying a given discrete data sample in multiple, non-commensurate dimensions. The algorithm works by constructing a metric-independent tessellation of the data space based on a recursive binary splitting. Individual, data-driven bandwidths are assigned to each point, scaled so that a constant “mass”M is enclosed. Kernel density estimation may then be performed for different kernel shapes, and a combination of balloon and sample point estimators is proposed as a compromise between resolution and variance. A bias correction is evaluated for the particular (yet common) case where the density is computed exactly at the locations of the data points rather than at an uncorrelated set of locations. By default, the algorithm combines a top-hat kernel with M=2.0 with the balloon estimator and applies the corresponding bias correction. These settings are shown to yield reasonable results for a simple test case, a two-dimensional ring, that illustrates the performance for oblique distributions, as well as for a six-dimensional Hernquist sphere, a fairly realistic model of the dynamical structure of stellar bulges in galaxies and dark matter haloes in cosmological N-body simulations. Results for different parameter settings are discussed in order to provide a guideline to select an optimal configuration in other cases. Source code is available upon request.
Estimated Probability of a Cervical Spine Injury During an ISS Mission
NASA Technical Reports Server (NTRS)
Brooker, John E.; Weaver, Aaron S.; Myers, Jerry G.
2013-01-01
Introduction: The Integrated Medical Model (IMM) utilizes historical data, cohort data, and external simulations as input factors to provide estimates of crew health, resource utilization and mission outcomes. The Cervical Spine Injury Module (CSIM) is an external simulation designed to provide the IMM with parameter estimates for 1) a probability distribution function (PDF) of the incidence rate, 2) the mean incidence rate, and 3) the standard deviation associated with the mean resulting from injury/trauma of the neck. Methods: An injury mechanism based on an idealized low-velocity blunt impact to the superior posterior thorax of an ISS crewmember was used as the simulated mission environment. As a result of this impact, the cervical spine is inertially loaded from the mass of the head producing an extension-flexion motion deforming the soft tissues of the neck. A multibody biomechanical model was developed to estimate the kinematic and dynamic response of the head-neck system from a prescribed acceleration profile. Logistic regression was performed on a dataset containing AIS1 soft tissue neck injuries from rear-end automobile collisions with published Neck Injury Criterion values producing an injury transfer function (ITF). An injury event scenario (IES) was constructed such that crew 1 is moving through a primary or standard translation path transferring large volume equipment impacting stationary crew 2. The incidence rate for this IES was estimated from in-flight data and used to calculate the probability of occurrence. The uncertainty in the model input factors were estimated from representative datasets and expressed in terms of probability distributions. A Monte Carlo Method utilizing simple random sampling was employed to propagate both aleatory and epistemic uncertain factors. Scatterplots and partial correlation coefficients (PCC) were generated to determine input factor sensitivity. CSIM was developed in the SimMechanics/Simulink environment with a
NASA Astrophysics Data System (ADS)
Kim, Kyu Rang; Kim, Mijin; Choe, Ho-Seong; Han, Mae Ja; Lee, Hye-Rim; Oh, Jae-Won; Kim, Baek-Jo
2016-07-01
Pollen is an important cause of respiratory allergic reactions. As individual sanitation has improved, allergy risk has increased, and this trend is expected to continue due to climate change. Atmospheric pollen concentration is highly influenced by weather conditions. Regression analysis and modeling of the relationships between airborne pollen concentrations and weather conditions were performed to analyze and forecast pollen conditions. Traditionally, daily pollen concentration has been estimated using regression models that describe the relationships between observed pollen concentrations and weather conditions. These models were able to forecast daily concentrations at the sites of observation, but lacked broader spatial applicability beyond those sites. To overcome this limitation, an integrated modeling scheme was developed that is designed to represent the underlying processes of pollen production and distribution. A maximum potential for airborne pollen is first determined using the Weibull probability density function. Then, daily pollen concentration is estimated using multiple regression models. Daily risk grade levels are determined based on the risk criteria used in Korea. The mean percentages of agreement between the observed and estimated levels were 81.4-88.2 % and 92.5-98.5 % for oak and Japanese hop pollens, respectively. The new models estimated daily pollen risk more accurately than the original statistical models because of the newly integrated biological response curves. Although they overestimated seasonal mean concentration, they did not simulate all of the peak concentrations. This issue would be resolved by adding more variables that affect the prevalence and internal maturity of pollens.
NASA Astrophysics Data System (ADS)
Kim, Kyu Rang; Kim, Mijin; Choe, Ho-Seong; Han, Mae Ja; Lee, Hye-Rim; Oh, Jae-Won; Kim, Baek-Jo
2017-02-01
Pollen is an important cause of respiratory allergic reactions. As individual sanitation has improved, allergy risk has increased, and this trend is expected to continue due to climate change. Atmospheric pollen concentration is highly influenced by weather conditions. Regression analysis and modeling of the relationships between airborne pollen concentrations and weather conditions were performed to analyze and forecast pollen conditions. Traditionally, daily pollen concentration has been estimated using regression models that describe the relationships between observed pollen concentrations and weather conditions. These models were able to forecast daily concentrations at the sites of observation, but lacked broader spatial applicability beyond those sites. To overcome this limitation, an integrated modeling scheme was developed that is designed to represent the underlying processes of pollen production and distribution. A maximum potential for airborne pollen is first determined using the Weibull probability density function. Then, daily pollen concentration is estimated using multiple regression models. Daily risk grade levels are determined based on the risk criteria used in Korea. The mean percentages of agreement between the observed and estimated levels were 81.4-88.2 % and 92.5-98.5 % for oak and Japanese hop pollens, respectively. The new models estimated daily pollen risk more accurately than the original statistical models because of the newly integrated biological response curves. Although they overestimated seasonal mean concentration, they did not simulate all of the peak concentrations. This issue would be resolved by adding more variables that affect the prevalence and internal maturity of pollens.
Fisicaro, E; Braibanti, A; Sambasiva Rao, R; Compari, C; Ghiozzi, A; Nageswara Rao, G
1998-04-01
An algorithm is proposed for the estimation of binding parameters for the interaction of biologically important macromolecules with smaller ones from electrometric titration data. The mathematical model is based on the representation of equilibria in terms of probability concepts of statistical molecular thermodynamics. The refinement of equilibrium concentrations of the components and estimation of binding parameters (log site constant and cooperativity factor) is performed using singular value decomposition, a chemometric technique which overcomes the general obstacles due to near singularity. The present software is validated with a number of biochemical systems of varying number of sites and cooperativity factors. The effect of random errors of realistic magnitude in experimental data is studied using the simulated primary data for some typical systems. The safe area within which approximate binding parameters ensure convergence has been reported for the non-self starting optimization algorithms.
Crowe, D.E.; Longshore, K.M.
2010-01-01
We estimated relative abundance and density of Western Burrowing Owls (Athene cunicularia hypugaea) at two sites in the Mojave Desert (200304). We made modifications to previously established Burrowing Owl survey techniques for use in desert shrublands and evaluated several factors that might influence the detection of owls. We tested the effectiveness of the call-broadcast technique for surveying this species, the efficiency of this technique at early and late breeding stages, and the effectiveness of various numbers of vocalization intervals during broadcasting sessions. Only 1 (3) of 31 initial (new) owl responses was detected during passive-listening sessions. We found that surveying early in the nesting season was more likely to produce new owl detections compared to surveying later in the nesting season. New owls detected during each of the three vocalization intervals (each consisting of 30 sec of vocalizations followed by 30 sec of silence) of our broadcasting session were similar (37, 40, and 23; n 30). We used a combination of detection trials (sighting probability) and double-observer method to estimate the components of detection probability, i.e., availability and perception. Availability for all sites and years, as determined by detection trials, ranged from 46.158.2. Relative abundance, measured as frequency of occurrence and defined as the proportion of surveys with at least one owl, ranged from 19.232.0 for both sites and years. Density at our eastern Mojave Desert site was estimated at 0.09 ?? 0.01 (SE) owl territories/km2 and 0.16 ?? 0.02 (SE) owl territories/km2 during 2003 and 2004, respectively. In our southern Mojave Desert site, density estimates were 0.09 ?? 0.02 (SE) owl territories/km2 and 0.08 ?? 0.02 (SE) owl territories/km 2 during 2004 and 2005, respectively. ?? 2010 The Raptor Research Foundation, Inc.
Development of a statistical tool for the estimation of riverbank erosion probability
NASA Astrophysics Data System (ADS)
Varouchakis, Emmanouil
2016-04-01
Riverbank erosion affects river morphology and local habitat, and results in riparian land loss, property and infrastructure damage, and ultimately flood defence weakening. An important issue concerning riverbank erosion is the identification of the vulnerable areas in order to predict river changes and assist stream management/restoration. An approach to predict areas vulnerable to erosion is to quantify the erosion probability by identifying the underlying relations between riverbank erosion and geomorphological or hydrological variables that prevent or stimulate erosion. In the present work, a innovative statistical methodology is proposed to predict the probability of presence or absence of erosion in a river section. A physically based model determines the locations vulnerable to erosion by quantifying the potential eroded area. The derived results are used to determine validation locations for the evaluation of the statistical tool performance. The statistical tool is based on a series of independent local variables and employs the Logistic Regression methodology. It is developed in two forms, Logistic Regression and Locally Weighted Logistic Regression, which both deliver useful and accurate results. The second form though, provides the most accurate results as it validates the presence or absence of erosion at all validation locations. The proposed tool is easy to use, accurate and can be applied to any region and river. Varouchakis, E. A., Giannakis, G. V., Lilli, M. A., Ioannidou, E., Nikolaidis, N. P., and Karatzas, G. P.: Development of a statistical tool for the estimation of riverbank erosion probability, SOIL (EGU), in print, 2016.
Toward 3D-guided prostate biopsy target optimization: an estimation of tumor sampling probabilities
NASA Astrophysics Data System (ADS)
Martin, Peter R.; Cool, Derek W.; Romagnoli, Cesare; Fenster, Aaron; Ward, Aaron D.
2014-03-01
Magnetic resonance imaging (MRI)-targeted, 3D transrectal ultrasound (TRUS)-guided "fusion" prostate biopsy aims to reduce the ~23% false negative rate of clinical 2D TRUS-guided sextant biopsy. Although it has been reported to double the positive yield, MRI-targeted biopsy still yields false negatives. Therefore, we propose optimization of biopsy targeting to meet the clinician's desired tumor sampling probability, optimizing needle targets within each tumor and accounting for uncertainties due to guidance system errors, image registration errors, and irregular tumor shapes. We obtained multiparametric MRI and 3D TRUS images from 49 patients. A radiologist and radiology resident contoured 81 suspicious regions, yielding 3D surfaces that were registered to 3D TRUS. We estimated the probability, P, of obtaining a tumor sample with a single biopsy. Given an RMS needle delivery error of 3.5 mm for a contemporary fusion biopsy system, P >= 95% for 21 out of 81 tumors when the point of optimal sampling probability was targeted. Therefore, more than one biopsy core must be taken from 74% of the tumors to achieve P >= 95% for a biopsy system with an error of 3.5 mm. Our experiments indicated that the effect of error along the needle axis on the percentage of core involvement (and thus the measured tumor burden) was mitigated by the 18 mm core length.
How Many Significant Figures are Useful for Public Risk Estimates?
NASA Astrophysics Data System (ADS)
Wilde, Paul D.; Duffy, Jim
2013-09-01
This paper considers the level of uncertainty in the calculation of public risks from launch or reentry and provides guidance on the number of significant digits that can be used with confidence when reporting the analysis results to decision-makers. The focus of this paper is the uncertainty in collective risk calculations that are used for launches of new and mature ELVs. This paper examines the computational models that are used to estimate total collective risk to the public for a launch, including the model input data and the model results, and characterizes the uncertainties due to both bias and variability. There have been two recent efforts to assess the uncertainty in state-of-the-art risk analysis models used in the US and their input data. One assessment focused on launch area risk from an Atlas V at Vandenberg Air Force Base (VAFB) and the other focused on downrange risk to Eurasia from a Falcon 9 launched from Cape Canaveral Air Force Station (CCAFS). The results of these studies quantified the uncertainties related to both the probability and the consequence of the launch debris hazards. This paper summarizes the results of both of these relatively comprehensive launch risk uncertainty analyses, which addressed both aleatory and epistemic uncertainties. The epistemic uncertainties of most concern were associated with probability of failure and the debris list. Other major sources of uncertainty evaluated were: the casualty area for people in shelters that are impacted by debris, impact distribution size, yield from exploding propellant and propellant tanks, probability of injury from a blast wave for people in shelters or outside, and population density. This paper also summarizes a relatively comprehensive over-flight risk uncertainty analysis performed by the FAA for the second stage of flight for a Falcon 9 from CCAFS. This paper is applicable to baseline collective risk analyses, such as those used to make a commercial license determination, and
Tillery, Anne C.; Matherne, Anne Marie; Verdin, Kristine L.
2012-01-01
In May and June 2012, the Whitewater-Baldy Fire burned approximately 1,200 square kilometers (300,000 acres) of the Gila National Forest, in southwestern New Mexico. The burned landscape is now at risk of damage from postwildfire erosion, such as that caused by debris flows and flash floods. This report presents a preliminary hazard assessment of the debris-flow potential from 128 basins burned by the Whitewater-Baldy Fire. A pair of empirical hazard-assessment models developed by using data from recently burned basins throughout the intermountain Western United States was used to estimate the probability of debris-flow occurrence and volume of debris flows along the burned area drainage network and for selected drainage basins within the burned area. The models incorporate measures of areal burned extent and severity, topography, soils, and storm rainfall intensity to estimate the probability and volume of debris flows following the fire. In response to the 2-year-recurrence, 30-minute-duration rainfall, modeling indicated that four basins have high probabilities of debris-flow occurrence (greater than or equal to 80 percent). For the 10-year-recurrence, 30-minute-duration rainfall, an additional 14 basins are included, and for the 25-year-recurrence, 30-minute-duration rainfall, an additional eight basins, 20 percent of the total, have high probabilities of debris-flow occurrence. In addition, probability analysis along the stream segments can identify specific reaches of greatest concern for debris flows within a basin. Basins with a high probability of debris-flow occurrence were concentrated in the west and central parts of the burned area, including tributaries to Whitewater Creek, Mineral Creek, and Willow Creek. Estimated debris-flow volumes ranged from about 3,000-4,000 cubic meters (m3) to greater than 500,000 m3 for all design storms modeled. Drainage basins with estimated volumes greater than 500,000 m3 included tributaries to Whitewater Creek, Willow
NASA Astrophysics Data System (ADS)
Morrow, P.; McCloskey, J.; Steacy, S.
2001-12-01
It is now widely accepted that the goal of deterministic earthquake prediction is unattainable in the short term and may even be forbidden by nonlinearity in the generating dynamics. This nonlinearity does not, however, preclude the estimation of earthquake probability and, in particular, how this probability might change in space and time; earthquake hazard estimation might be possible in the absence of earthquake prediction. Recently, there has been a major development in the understanding of stress triggering of earthquakes which allows accurate calculation of the spatial variation of aftershock probability following any large earthquake. Over the past few years this Coulomb stress technique (CST) has been the subject of intensive study in the geophysics literature and has been extremely successful in explaining the spatial distribution of aftershocks following several major earthquakes. The power of current micro-computers, the great number of local, telemetered seismic networks, the rapid acquisition of data from satellites coupled with the speed of modern telecommunications and data transfer all mean that it may be possible that these new techniques could be applied in a forward sense. In other words, it is theoretically possible today to make predictions of the likely spatial distribution of aftershocks in near-real-time following a large earthquake. Approximate versions of such predictions could be available within, say, 0.1 days after the mainshock and might be continually refined and updated over the next 100 days. The European Commission has recently provided funding for a project to assess the extent to which it is currently possible to move CST predictions into a practically useful time frame so that low-confidence estimates of aftershock probability might be made within a few hours of an event and improved in near-real-time, as data of better quality become available over the following days to tens of days. Specifically, the project aims to assess the
Rajwade, Ajit; Banerjee, Arunava; Rangarajan, Anand
2009-03-01
We present a new, geometric approach for determining the probability density of the intensity values in an image. We drop the notion of an image as a set of discrete pixels, and assume a piecewise-continuous representation. The probability density can then be regarded as being proportional to the area between two nearby isocontours of the image surface. Our paper extends this idea to joint densities of image pairs. We demonstrate the application of our method to affine registration between two or more images using information theoretic measures such as mutual information. We show cases where our method outperforms existing methods such as simple histograms, histograms with partial volume interpolation, Parzen windows, etc. under fine intensity quantization for affine image registration under significant image noise. Furthermore, we demonstrate results on simultaneous registration of multiple images, as well as for pairs of volume datasets, and show some theoretical properties of our density estimator. Our approach requires the selection of only an image interpolant. The method neither requires any kind of kernel functions (as in Parzen windows) which are unrelated to the structure of the image in itself, nor does it rely on any form of sampling for density estimation.
Rajwade, Ajit; Banerjee, Arunava; Rangarajan, Anand
2010-01-01
We present a new geometric approach for determining the probability density of the intensity values in an image. We drop the notion of an image as a set of discrete pixels and assume a piecewise-continuous representation. The probability density can then be regarded as being proportional to the area between two nearby isocontours of the image surface. Our paper extends this idea to joint densities of image pairs. We demonstrate the application of our method to affine registration between two or more images using information-theoretic measures such as mutual information. We show cases where our method outperforms existing methods such as simple histograms, histograms with partial volume interpolation, Parzen windows, etc., under fine intensity quantization for affine image registration under significant image noise. Furthermore, we demonstrate results on simultaneous registration of multiple images, as well as for pairs of volume data sets, and show some theoretical properties of our density estimator. Our approach requires the selection of only an image interpolant. The method neither requires any kind of kernel functions (as in Parzen windows), which are unrelated to the structure of the image in itself, nor does it rely on any form of sampling for density estimation. PMID:19147876
Kruppa, Jochen; Liu, Yufeng; Diener, Hans-Christian; Holste, Theresa; Weimar, Christian; König, Inke R; Ziegler, Andreas
2014-07-01
Machine learning methods are applied to three different large datasets, all dealing with probability estimation problems for dichotomous or multicategory data. Specifically, we investigate k-nearest neighbors, bagged nearest neighbors, random forests for probability estimation trees, and support vector machines with the kernels of Bessel, linear, Laplacian, and radial basis type. Comparisons are made with logistic regression. The dataset from the German Stroke Study Collaboration with dichotomous and three-category outcome variables allows, in particular, for temporal and external validation. The other two datasets are freely available from the UCI learning repository and provide dichotomous outcome variables. One of them, the Cleveland Clinic Foundation Heart Disease dataset, uses data from one clinic for training and from three clinics for external validation, while the other, the thyroid disease dataset, allows for temporal validation by separating data into training and test data by date of recruitment into study. For dichotomous outcome variables, we use receiver operating characteristics, areas under the curve values with bootstrapped 95% confidence intervals, and Hosmer-Lemeshow-type figures as comparison criteria. For dichotomous and multicategory outcomes, we calculated bootstrap Brier scores with 95% confidence intervals and also compared them through bootstrapping. In a supplement, we provide R code for performing the analyses and for random forest analyses in Random Jungle, version 2.1.0. The learning machines show promising performance over all constructed models. They are simple to apply and serve as an alternative approach to logistic or multinomial logistic regression analysis.
Fast method for the estimation of impact probability of near-Earth objects
NASA Astrophysics Data System (ADS)
Vavilov, D.; Medvedev, Y.
2014-07-01
We propose a method to estimate the probability of collision of a celestial body with the Earth (or another major planet) at a given time moment t. Let there be a set of observations of a small body. At initial time moment T_0, a nominal orbit is defined by the least squares method. In our method, a unique coordinate system is used. It is supposed that errors of observations are related to errors of coordinates and velocities linearly and the distribution law of observation errors is normal. The unique frame is defined as follows. First of all, we fix an osculating ellipse of the body's orbit at the time moment t. The mean anomaly M in this osculating ellipse is a coordinate of the introduced system. The spatial coordinate ξ is perpendicular to the plane which contains the fixed ellipse. η is a spatial coordinate, too, and our axes satisfy the right-hand rule. The origin of ξ and η corresponds to the given M point on the ellipse. The components of the velocity are the corresponding derivatives of dotξ, dotη, dot{M}. To calculate the probability of collision, we numerically integrate equations of an asteroid's motion taking into account perturbations and calculate a normal matrix N. The probability is determinated as follows: P = {|detN|^{ {1}/{2} }}/{ (2π)^3 } int_Ω e^{ - {1}/{2} x^T N x } dx where x denotes a six-dimensional vector of coordinates and velocities, Ω is the region which is occupied by the Earth, and the superscript T denotes the matrix transpose operation. To take into account a gravitational attraction of the Earth, the radius of the Earth is increased by √{1 + {v_s^2}/{v_{rel}^2} } times, where v_s is the escape velocity and v_{rel} is the small body's velocity relative to the Earth. The 6-dimensional integral is analytically integrated over the velocity components on (-∞,+∞). After that we have the 3×3 matrix N_1. That 6-dimensional integral becomes a 3-dimensional integral. To calculate it quickly we do the following. We introduce
Estimating Non-stationary Flood Risk in a Changing Climate
NASA Astrophysics Data System (ADS)
Yu, X.; Cohn, T. A.; Stedinger, J. R.
2015-12-01
Flood risk is usually described by a probability distribution for annual maximum streamflow which is assumed not to change with time. Federal, state and local governments in the United States are demanding guidance on flood frequency estimates that account for climate change. If a trend exists in peak flow series, ignoring it could result in large quantile estimator bias, while trying to estimate a trend will increase the flood quantile estimator's variance. Thus the issue is, what bias-variance tradeoff should we accept? This paper discusses approaches to flood frequency analysis (FFA) when flood series have trends. GCMs describe how annual runoff might vary over sub-continental scales, but this information is nearly useless for FFA in small watersheds. A LP3 Monte Carlo analysis and a re-sampling study of 100-year flood estimation (25- and 50-year projections) compares the performance of five methods: FFA as prescribed in national guidelines (Bulletin 17B), assumes the flood series is stationary and follows a log-Pearson type III (LP3) distribution; Fitting a LP3 distribution with time-varying parameters that include future trends in mean and perhaps variance, where slopes are assumed known; Fitting a LP3 distribution with time-varying parameters that capture future trends in mean and perhaps variance, where slopes are estimated from annual peak flow series; Employing only the most recent 30 years of flood records to fit a LP3 distribution; Applying a safety factor to the 100-year flood estimator (e.g. 25% increase). The 100-year flood estimator of method 2 has the smallest log-space mean squared error, though it is unlikely that the true trend would be known. Method 3 is only recommended over method 1 for large trends (≥ 0.5% per year). The 100-year flood estimators of method 1, 4, and 5 often have poor accuracy. Clearly, flood risk assessment will be a challenge in an uncertain world.
Estimating Probabilities of Peptide Database Identifications to LC-FTICR-MS Observations
Anderson, Kevin K.; Monroe, Matthew E.; Daly, Don S.
2006-02-24
One of the grand challenges in the post-genomic era is proteomics, the characterization of the proteins expressed in a cell under specific conditions. A promising technology for high-throughput proteomics is mass spectrometry, specifically liquid chromatography coupled to Fourier transform ion cyclotron resonance mass spectrometry (LC-FTICR-MS). The accuracy and certainty of the determinations of peptide identities and abundances provided by LC-FTICR-MS are an important and necessary component of systems biology research. Methods: After a tryptically digested protein mixture is analyzed by LC-FTICR-MS, the observed masses and normalized elution times of the detected features are statistically matched to the theoretical masses and elution times of known peptides listed in a large database. The probability of matching is estimated for each peptide in the reference database using statistical classification methods assuming bivariate Gaussian probability distributions on the uncertainties in the masses and the normalized elution times. A database of 69,220 features from 32 LC-FTICR-MS analyses of a tryptically digested bovine serum albumin (BSA) sample was matched to a database populated with 97% false positive peptides. The percentage of high confidence identifications was found to be consistent with other database search procedures. BSA database peptides were identified with high confidence on average in 14.1 of the 32 analyses. False positives were identified on average in just 2.7 analyses. Using a priori probabilities that contrast peptides from expected and unexpected proteins was shown to perform better in identifying target peptides than using equally likely a priori probabilities. This is because a large percentage of the target peptides were similar to unexpected peptides which were included to be false positives. The use of triplicate analyses with a ''2 out of 3'' reporting rule was shown to have excellent rejection of false positives.
NASA Astrophysics Data System (ADS)
Abadie, Luis Maria; Galarraga, Ibon; Sainz de Murieta, Elisa
2017-01-01
A quantification of present and future mean annual losses due to extreme coastal events can be crucial for adequate decision making on adaptation to climate change in coastal areas around the globe. However, this approach is limited when uncertainty needs to be accounted for. In this paper, we assess coastal flood risk from sea-level rise and extreme events in 120 major cities around the world using an alternative stochastic approach that accounts for uncertainty. Probability distributions of future relative (local) sea-level rise have been used for each city, under three IPPC emission scenarios, RCP 2.6, 4.5 and 8.5. The approach allows a continuous stochastic function to be built to assess yearly evolution of damages from 2030 to 2100. Additionally, we present two risk measures that put low-probability, high-damage events in the spotlight: the Value at Risk (VaR) and the Expected Shortfall (ES), which enable the damages to be estimated when a certain risk level is exceeded. This level of acceptable risk can be defined involving different stakeholders to guide progressive adaptation strategies. The method presented here is new in the field of economics of adaptation and offers a much broader picture of the challenges related to dealing with climate impacts. Furthermore, it can be applied to assess not only adaptation needs but also to put adaptation into a timeframe in each city.
A methodology for estimating risks associated with landslides of contaminated soil into rivers.
Göransson, Gunnel; Norrman, Jenny; Larson, Magnus; Alén, Claes; Rosén, Lars
2014-02-15
Urban areas adjacent to surface water are exposed to soil movements such as erosion and slope failures (landslides). A landslide is a potential mechanism for mobilisation and spreading of pollutants. This mechanism is in general not included in environmental risk assessments for contaminated sites, and the consequences associated with contamination in the soil are typically not considered in landslide risk assessments. This study suggests a methodology to estimate the environmental risks associated with landslides in contaminated sites adjacent to rivers. The methodology is probabilistic and allows for datasets with large uncertainties and the use of expert judgements, providing quantitative estimates of probabilities for defined failures. The approach is illustrated by a case study along the river Göta Älv, Sweden, where failures are defined and probabilities for those failures are estimated. Failures are defined from a pollution perspective and in terms of exceeding environmental quality standards (EQSs) and acceptable contaminant loads. Models are then suggested to estimate probabilities of these failures. A landslide analysis is carried out to assess landslide probabilities based on data from a recent landslide risk classification study along the river Göta Älv. The suggested methodology is meant to be a supplement to either landslide risk assessment (LRA) or environmental risk assessment (ERA), providing quantitative estimates of the risks associated with landslide in contaminated sites. The proposed methodology can also act as a basis for communication and discussion, thereby contributing to intersectoral management solutions. From the case study it was found that the defined failures are governed primarily by the probability of a landslide occurring. The overall probabilities for failure are low; however, if a landslide occurs the probabilities of exceeding EQS are high and the probability of having at least a 10% increase in the contamination load
Fast and accurate probability density estimation in large high dimensional astronomical datasets
NASA Astrophysics Data System (ADS)
Gupta, Pramod; Connolly, Andrew J.; Gardner, Jeffrey P.
2015-01-01
Astronomical surveys will generate measurements of hundreds of attributes (e.g. color, size, shape) on hundreds of millions of sources. Analyzing these large, high dimensional data sets will require efficient algorithms for data analysis. An example of this is probability density estimation that is at the heart of many classification problems such as the separation of stars and quasars based on their colors. Popular density estimation techniques use binning or kernel density estimation. Kernel density estimation has a small memory footprint but often requires large computational resources. Binning has small computational requirements but usually binning is implemented with multi-dimensional arrays which leads to memory requirements which scale exponentially with the number of dimensions. Hence both techniques do not scale well to large data sets in high dimensions. We present an alternative approach of binning implemented with hash tables (BASH tables). This approach uses the sparseness of data in the high dimensional space to ensure that the memory requirements are small. However hashing requires some extra computation so a priori it is not clear if the reduction in memory requirements will lead to increased computational requirements. Through an implementation of BASH tables in C++ we show that the additional computational requirements of hashing are negligible. Hence this approach has small memory and computational requirements. We apply our density estimation technique to photometric selection of quasars using non-parametric Bayesian classification and show that the accuracy of the classification is same as the accuracy of earlier approaches. Since the BASH table approach is one to three orders of magnitude faster than the earlier approaches it may be useful in various other applications of density estimation in astrostatistics.
Hart, Stephen D; Cooke, David J
2013-01-01
We investigated the precision of individual risk estimates made using actuarial risk assessment instruments (ARAIs) by discussing some major conceptual issues and then illustrating them by analyzing new data. We used a standard multivariate statistical procedure, logistic regression, to create a new ARAI based on data from a follow-up study of 90 adult male sex offenders. We indexed predictive precision at the group level using confidence intervals for group mean probability estimates, and at the individual level using prediction intervals for individual probability estimates. Consistent with past research, ARAI scores were moderately and significantly predictive of failure in the aggregate, but group probability estimates had substantial margins of error and individual probability estimates had very large margins of error. We conclude that, without major advances in our understanding of the causes of violence, ARAIs cannot be used to estimate the specific probability or absolute likelihood of future violence with any reasonable degree of precision or certainty. The implications for conducting violence risk assessments in forensic mental health are discussed.
Auditory risk estimates for youth target shooting
Meinke, Deanna K.; Murphy, William J.; Finan, Donald S.; Lankford, James E.; Flamme, Gregory A.; Stewart, Michael; Soendergaard, Jacob; Jerome, Trevor W.
2015-01-01
Objective To characterize the impulse noise exposure and auditory risk for youth recreational firearm users engaged in outdoor target shooting events. The youth shooting positions are typically standing or sitting at a table, which places the firearm closer to the ground or reflective surface when compared to adult shooters. Design Acoustic characteristics were examined and the auditory risk estimates were evaluated using contemporary damage-risk criteria for unprotected adult listeners and the 120-dB peak limit suggested by the World Health Organization (1999) for children. Study sample Impulses were generated by 26 firearm/ammunition configurations representing rifles, shotguns, and pistols used by youth. Measurements were obtained relative to a youth shooter’s left ear. Results All firearms generated peak levels that exceeded the 120 dB peak limit suggested by the WHO for children. In general, shooting from the seated position over a tabletop increases the peak levels, LAeq8 and reduces the unprotected maximum permissible exposures (MPEs) for both rifles and pistols. Pistols pose the greatest auditory risk when fired over a tabletop. Conclusion Youth should utilize smaller caliber weapons, preferably from the standing position, and always wear hearing protection whenever engaging in shooting activities to reduce the risk for auditory damage. PMID:24564688
NASA Astrophysics Data System (ADS)
Cavuoti, S.; Amaro, V.; Brescia, M.; Vellucci, C.; Tortora, C.; Longo, G.
2017-02-01
A variety of fundamental astrophysical science topics require the determination of very accurate photometric redshifts (photo-z). A wide plethora of methods have been developed, based either on template models fitting or on empirical explorations of the photometric parameter space. Machine-learning-based techniques are not explicitly dependent on the physical priors and able to produce accurate photo-z estimations within the photometric ranges derived from the spectroscopic training set. These estimates, however, are not easy to characterize in terms of a photo-z probability density function (PDF), due to the fact that the analytical relation mapping the photometric parameters on to the redshift space is virtually unknown. We present METAPHOR (Machine-learning Estimation Tool for Accurate PHOtometric Redshifts), a method designed to provide a reliable PDF of the error distribution for empirical techniques. The method is implemented as a modular workflow, whose internal engine for photo-z estimation makes use of the MLPQNA neural network (Multi Layer Perceptron with Quasi Newton learning rule), with the possibility to easily replace the specific machine-learning model chosen to predict photo-z. We present a summary of results on SDSS-DR9 galaxy data, used also to perform a direct comparison with PDFs obtained by the LE PHARE spectral energy distribution template fitting. We show that METAPHOR is capable to estimate the precision and reliability of photometric redshifts obtained with three different self-adaptive techniques, i.e. MLPQNA, Random Forest and the standard K-Nearest Neighbors models.
Lin, Feng; Chen, Xinguang
2009-01-01
In order to find better strategies for tobacco control, it is often critical to know the transitional probabilities among various stages of tobacco use. Traditionally, such probabilities are estimated by analyzing data from longitudinal surveys that are often time-consuming and expensive to conduct. Since cross-sectional surveys are much easier to conduct, it will be much more practical and useful to estimate transitional probabilities from cross-sectional survey data if possible. However, no previous research has attempted to do this. In this paper, we propose a method to estimate transitional probabilities from cross-sectional survey data. The method is novel and is based on a discrete event system framework. In particular, we introduce state probabilities and transitional probabilities to conventional discrete event system models. We derive various equations that can be used to estimate the transitional probabilities. We test the method using cross-sectional data of the National Survey on Drug Use and Health. The estimated transitional probabilities can be used in predicting the future smoking behavior for decision-making, planning and evaluation of various tobacco control programs. The method also allows a sensitivity analysis that can be used to find the most effective way of tobacco control. Since there are much more cross-sectional survey data in existence than longitudinal ones, the impact of this new method is expected to be significant. PMID:20161437
ANNz2: Photometric Redshift and Probability Distribution Function Estimation using Machine Learning
NASA Astrophysics Data System (ADS)
Sadeh, I.; Abdalla, F. B.; Lahav, O.
2016-10-01
We present ANNz2, a new implementation of the public software for photometric redshift (photo-z) estimation of Collister & Lahav, which now includes generation of full probability distribution functions (PDFs). ANNz2 utilizes multiple machine learning methods, such as artificial neural networks and boosted decision/regression trees. The objective of the algorithm is to optimize the performance of the photo-z estimation, to properly derive the associated uncertainties, and to produce both single-value solutions and PDFs. In addition, estimators are made available, which mitigate possible problems of non-representative or incomplete spectroscopic training samples. ANNz2 has already been used as part of the first weak lensing analysis of the Dark Energy Survey, and is included in the experiment's first public data release. Here we illustrate the functionality of the code using data from the tenth data release of the Sloan Digital Sky Survey and the Baryon Oscillation Spectroscopic Survey. The code is available for download at http://github.com/IftachSadeh/ANNZ.
Methods for estimating dispersal probabilities and related parameters using marked animals
Bennetts, R.E.; Nichols, J.D.; Pradel, R.; Lebreton, J.D.; Kitchens, W.M.; Clobert, Jean; Danchin, Etienne; Dhondt, Andre A.; Nichols, James D.
2001-01-01
Deriving valid inferences about the causes and consequences of dispersal from empirical studies depends largely on our ability reliably to estimate parameters associated with dispersal. Here, we present a review of the methods available for estimating dispersal and related parameters using marked individuals. We emphasize methods that place dispersal in a probabilistic framework. In this context, we define a dispersal event as a movement of a specified distance or from one predefined patch to another, the magnitude of the distance or the definition of a `patch? depending on the ecological or evolutionary question(s) being addressed. We have organized the chapter based on four general classes of data for animals that are captured, marked, and released alive: (1) recovery data, in which animals are recovered dead at a subsequent time, (2) recapture/resighting data, in which animals are either recaptured or resighted alive on subsequent sampling occasions, (3) known-status data, in which marked animals are reobserved alive or dead at specified times with probability 1.0, and (4) combined data, in which data are of more than one type (e.g., live recapture and ring recovery). For each data type, we discuss the data required, the estimation techniques, and the types of questions that might be addressed from studies conducted at single and multiple sites.
SAR amplitude probability density function estimation based on a generalized Gaussian model.
Moser, Gabriele; Zerubia, Josiane; Serpico, Sebastiano B
2006-06-01
In the context of remotely sensed data analysis, an important problem is the development of accurate models for the statistics of the pixel intensities. Focusing on synthetic aperture radar (SAR) data, this modeling process turns out to be a crucial task, for instance, for classification or for denoising purposes. In this paper, an innovative parametric estimation methodology for SAR amplitude data is proposed that adopts a generalized Gaussian (GG) model for the complex SAR backscattered signal. A closed-form expression for the corresponding amplitude probability density function (PDF) is derived and a specific parameter estimation algorithm is developed in order to deal with the proposed model. Specifically, the recently proposed "method-of-log-cumulants" (MoLC) is applied, which stems from the adoption of the Mellin transform (instead of the usual Fourier transform) in the computation of characteristic functions and from the corresponding generalization of the concepts of moment and cumulant. For the developed GG-based amplitude model, the resulting MoLC estimates turn out to be numerically feasible and are also analytically proved to be consistent. The proposed parametric approach was validated by using several real ERS-1, XSAR, E-SAR, and NASA/JPL airborne SAR images, and the experimental results prove that the method models the amplitude PDF better than several previously proposed parametric models for backscattering phenomena.
The report evaluates approaches for estimating the probability of ingestion by birds of contaminated particles such as pesticide granules or lead particles (i.e. shot or bullet fragments). In addition, it presents an approach for using this information to estimate the risk of mo...
NASA Astrophysics Data System (ADS)
Haigh, Ivan D.; Wijeratne, E. M. S.; MacPherson, Leigh R.; Pattiaratchi, Charitha B.; Mason, Matthew S.; Crompton, Ryan P.; George, Steve
2014-01-01
The occurrence of extreme water levels along low-lying, highly populated and/or developed coastlines can lead to considerable loss of life and billions of dollars of damage to coastal infrastructure. Therefore it is vitally important that the exceedance probabilities of extreme water levels are accurately evaluated to inform risk-based flood management, engineering and future land-use planning. This ensures the risk of catastrophic structural failures due to under-design or expensive wastes due to over-design are minimised. This paper estimates for the first time present day extreme water level exceedence probabilities around the whole coastline of Australia. A high-resolution depth averaged hydrodynamic model has been configured for the Australian continental shelf region and has been forced with tidal levels from a global tidal model and meteorological fields from a global reanalysis to generate a 61-year hindcast of water levels. Output from this model has been successfully validated against measurements from 30 tide gauge sites. At each numeric coastal grid point, extreme value distributions have been fitted to the derived time series of annual maxima and the several largest water levels each year to estimate exceedence probabilities. This provides a reliable estimate of water level probabilities around southern Australia; a region mainly impacted by extra-tropical cyclones. However, as the meteorological forcing used only weakly includes the effects of tropical cyclones, extreme water level probabilities are underestimated around the western, northern and north-eastern Australian coastline. In a companion paper we build on the work presented here and more accurately include tropical cyclone-induced surges in the estimation of extreme water level. The multi-decadal hindcast generated here has been used primarily to estimate extreme water level exceedance probabilities but could be used more widely in the future for a variety of other research and practical
A Model-Free Machine Learning Method for Risk Classification and Survival Probability Prediction.
Geng, Yuan; Lu, Wenbin; Zhang, Hao Helen
2014-01-01
Risk classification and survival probability prediction are two major goals in survival data analysis since they play an important role in patients' risk stratification, long-term diagnosis, and treatment selection. In this article, we propose a new model-free machine learning framework for risk classification and survival probability prediction based on weighted support vector machines. The new procedure does not require any specific parametric or semiparametric model assumption on data, and is therefore capable of capturing nonlinear covariate effects. We use numerous simulation examples to demonstrate finite sample performance of the proposed method under various settings. Applications to a glioma tumor data and a breast cancer gene expression survival data are shown to illustrate the new methodology in real data analysis.
Signor, R S; Ashbolt, N J
2009-12-01
Some national drinking water guidelines provide guidance on how to define 'safe' drinking water. Regarding microbial water quality, a common position is that the chance of an individual becoming infected by some reference waterborne pathogen (e.g. Cryptsporidium) present in the drinking water should < 10(-4) in any year. However the instantaneous levels of risk to a water consumer vary over the course of a year, and waterborne disease outbreaks have been associated with shorter-duration periods of heightened risk. Performing probabilistic microbial risk assessments is becoming commonplace to capture the impacts of temporal variability on overall infection risk levels. A case is presented here for adoption of a shorter-duration reference period (i.e. daily) infection probability target over which to assess, report and benchmark such risks. A daily infection probability benchmark may provide added incentive and guidance for exercising control over short-term adverse risk fluctuation events and their causes. Management planning could involve outlining measures so that the daily target is met under a variety of pre-identified event scenarios. Other benefits of a daily target could include providing a platform for managers to design and assess management initiatives, as well as simplifying the technical components of the risk assessment process.
Change of flood risk under climate change based on Discharge Probability Index in Japan
NASA Astrophysics Data System (ADS)
Nitta, T.; Yoshimura, K.; Kanae, S.; Oki, T.
2010-12-01
Water-related disasters under the climate change have recently gained considerable interest, and there have been many studies referring to flood risk at the global scale (e.g. Milly et al., 2002; Hirabayashi et al., 2008). In order to build adaptive capacity, however, regional impact evaluation is needed. We thus focus on the flood risk over Japan in the present study. The output from the Regional Climate Model 20 (RCM20), which was developed by the Meteorological Research Institute, was used. The data was first compared with observed data based on Automated Meteorological Data Acquisition System and ground weather observations, and the model biases were corrected using the ratio and difference of the 20-year mean values. The bias-corrected RCM20 atmospheric data were then forced to run a land surface model and a river routing model (Yoshimura et al., 2007; Ngo-Duc, T. et al. 2007) to simulate river discharge during 1981-2000, 2031-2050, and 2081-2100. Simulated river discharge was converted to Discharge Probability Index (DPI), which was proposed by Yoshimura et al based on a statistical approach. The bias and uncertainty of the models are already taken into account in the concept of DPI, so that DPI serves as a good indicator of flood risk. We estimated the statistical parameters for DPI using the river discharge for 1981-2000 with an assumption that the parameters stay the same in the different climate periods. We then evaluated the occurrence of flood events corresponding to DPI categories in each 20 years and averaged them in 9 regions. The results indicate that low DPI flood events (return period of 2 years) will become more frequent in 2031-2050 and high DPI flood events (return period of 200 years) will become more frequent in 2081-2100 compared with the period of 1981-2000, though average precipitation will become larger during 2031-2050 than during 2081-2100 in most regions. It reflects the increased extreme precipitation during 2081-2100.
Estimated Probability of Traumatic Abdominal Injury During an International Space Station Mission
NASA Technical Reports Server (NTRS)
Lewandowski, Beth E.; Brooker, John E.; Weavr, Aaron S.; Myers, Jerry G., Jr.; McRae, Michael P.
2013-01-01
The Integrated Medical Model (IMM) is a decision support tool that is useful to spaceflight mission planners and medical system designers when assessing risks and optimizing medical systems. The IMM project maintains a database of medical conditions that could occur during a spaceflight. The IMM project is in the process of assigning an incidence rate, the associated functional impairment, and a best and a worst case end state for each condition. The purpose of this work was to develop the IMM Abdominal Injury Module (AIM). The AIM calculates an incidence rate of traumatic abdominal injury per person-year of spaceflight on the International Space Station (ISS). The AIM was built so that the probability of traumatic abdominal injury during one year on ISS could be predicted. This result will be incorporated into the IMM Abdominal Injury Clinical Finding Form and used within the parent IMM model.
Estimating the probability for a protein to have a new fold: A statistical computational model
Portugaly, Elon; Linial, Michal
2000-01-01
Structural genomics aims to solve a large number of protein structures that represent the protein space. Currently an exhaustive solution for all structures seems prohibitively expensive, so the challenge is to define a relatively small set of proteins with new, currently unknown folds. This paper presents a method that assigns each protein with a probability of having an unsolved fold. The method makes extensive use of protomap, a sequence-based classification, and scop, a structure-based classification. According to protomap, the protein space encodes the relationship among proteins as a graph whose vertices correspond to 13,354 clusters of proteins. A representative fold for a cluster with at least one solved protein is determined after superposition of all scop (release 1.37) folds onto protomap clusters. Distances within the protomap graph are computed from each representative fold to the neighboring folds. The distribution of these distances is used to create a statistical model for distances among those folds that are already known and those that have yet to be discovered. The distribution of distances for solved/unsolved proteins is significantly different. This difference makes it possible to use Bayes' rule to derive a statistical estimate that any protein has a yet undetermined fold. Proteins that score the highest probability to represent a new fold constitute the target list for structural determination. Our predicted probabilities for unsolved proteins correlate very well with the proportion of new folds among recently solved structures (new scop 1.39 records) that are disjoint from our original training set. PMID:10792051
Measuring and Modeling Fault Density for Plume-Fault Encounter Probability Estimation
Jordan, P.D.; Oldenburg, C.M.; Nicot, J.-P.
2011-05-15
Emission of carbon dioxide from fossil-fueled power generation stations contributes to global climate change. Storage of this carbon dioxide within the pores of geologic strata (geologic carbon storage) is one approach to mitigating the climate change that would otherwise occur. The large storage volume needed for this mitigation requires injection into brine-filled pore space in reservoir strata overlain by cap rocks. One of the main concerns of storage in such rocks is leakage via faults. In the early stages of site selection, site-specific fault coverages are often not available. This necessitates a method for using available fault data to develop an estimate of the likelihood of injected carbon dioxide encountering and migrating up a fault, primarily due to buoyancy. Fault population statistics provide one of the main inputs to calculate the encounter probability. Previous fault population statistics work is shown to be applicable to areal fault density statistics. This result is applied to a case study in the southern portion of the San Joaquin Basin with the result that the probability of a carbon dioxide plume from a previously planned injection had a 3% chance of encountering a fully seal offsetting fault.
Smith, L.L.; Barichivich, W.J.; Staiger, J.S.; Smith, Kimberly G.; Dodd, C.K.
2006-01-01
We conducted an amphibian inventory at Okefenokee National Wildlife Refuge from August 2000 to June 2002 as part of the U.S. Department of the Interior's national Amphibian Research and Monitoring Initiative. Nineteen species of amphibians (15 anurans and 4 caudates) were documented within the Refuge, including one protected species, the Gopher Frog Rana capito. We also collected 1 y of monitoring data for amphibian populations and incorporated the results into the inventory. Detection probabilities and site occupancy estimates for four species, the Pinewoods Treefrog (Hyla femoralis), Pig Frog (Rana grylio), Southern Leopard Frog (R. sphenocephala) and Carpenter Frog (R. virgatipes) are presented here. Detection probabilities observed in this study indicate that spring and summer surveys offer the best opportunity to detect these species in the Refuge. Results of the inventory suggest that substantial changes may have occurred in the amphibian fauna within and adjacent to the swamp. However, monitoring the amphibian community of Okefenokee Swamp will prove difficult because of the logistical challenges associated with a rigorous statistical assessment of status and trends.
Adams, Vanessa M.; Pressey, Robert L.; Stoeckl, Natalie
2014-01-01
The need to integrate social and economic factors into conservation planning has become a focus of academic discussions and has important practical implications for the implementation of conservation areas, both private and public. We conducted a survey in the Daly Catchment, Northern Territory, to inform the design and implementation of a stewardship payment program. We used a choice model to estimate the likely level of participation in two legal arrangements - conservation covenants and management agreements - based on payment level and proportion of properties required to be managed. We then spatially predicted landholders’ probability of participating at the resolution of individual properties and incorporated these predictions into conservation planning software to examine the potential for the stewardship program to meet conservation objectives. We found that the properties that were least costly, per unit area, to manage were also the least likely to participate. This highlights a tension between planning for a cost-effective program and planning for a program that targets properties with the highest probability of participation. PMID:24892520
Estimation of the failure probability during EGS stimulation based on borehole data
NASA Astrophysics Data System (ADS)
Meller, C.; Kohl, Th.; Gaucher, E.
2012-04-01
In recent times the search for alternative sources of energy has been fostered by the scarcity of fossil fuels. With its ability to permanently provide electricity or heat with little emission of CO2, geothermal energy will have an important share in the energy mix of the future. Within Europe, scientists identified many locations with conditions suitable for Enhanced Geothermal System (EGS) projects. In order to provide sufficiently high reservoir permeability, EGS require borehole stimulations prior to installation of power plants (Gérard et al, 2006). Induced seismicity during water injection into reservoirs EGS systems is a factor that currently cannot be predicted nor controlled. Often, people living near EGS projects are frightened by smaller earthquakes occurring during stimulation or injection. As this fear can lead to widespread disapproval of geothermal power plants, it is appreciable to find a way to estimate the probability of fractures to shear when injecting water with a distinct pressure into a geothermal reservoir. This provides knowledge, which enables to predict the mechanical behavior of a reservoir in response to a change in pore pressure conditions. In the present study an approach for estimation of the shearing probability based on statistical analyses of fracture distribution, orientation and clusters, together with their geological properties is proposed. Based on geophysical logs of five wells in Soultz-sous-Forêts, France, and with the help of statistical tools, the Mohr criterion, geological and mineralogical properties of the host rock and the fracture fillings, correlations between the wells are analyzed. This is achieved with the self-written MATLAB-code Fracdens, which enables us to statistically analyze the log files in different ways. With the application of a pore pressure change, the evolution of the critical pressure on the fractures can be determined. A special focus is on the clay fillings of the fractures and how they reduce
Relating space radiation environments to risk estimates
NASA Technical Reports Server (NTRS)
Curtis, Stanley B.
1993-01-01
A number of considerations must go into the process of determining the risk of deleterious effects of space radiation to travelers. Among them are (1) determination of the components of the radiation environment (particle species, fluxes and energy spectra) which will encounter, (2) determination of the effects of shielding provided by the spacecraft and the bodies of the travelers which modify the incident particle spectra and mix of particles, and (3) determination of relevant biological effects of the radiation in the organs of interest. The latter can then lead to an estimation of risk from a given space scenario. Clearly, the process spans many scientific disciplines from solar and cosmic ray physics to radiation transport theeory to the multistage problem of the induction by radiation of initial lesions in living material and their evolution via physical, chemical, and biological processes at the molecular, cellular, and tissue levels to produce the end point of importance.
Neural response to reward anticipation under risk is nonlinear in probabilities.
Hsu, Ming; Krajbich, Ian; Zhao, Chen; Camerer, Colin F
2009-02-18
A widely observed phenomenon in decision making under risk is the apparent overweighting of unlikely events and the underweighting of nearly certain events. This violates standard assumptions in expected utility theory, which requires that expected utility be linear (objective) in probabilities. Models such as prospect theory have relaxed this assumption and introduced the notion of a "probability weighting function," which captures the key properties found in experimental data. This study reports functional magnetic resonance imaging (fMRI) data that neural response to expected reward is nonlinear in probabilities. Specifically, we found that activity in the striatum during valuation of monetary gambles are nonlinear in probabilities in the pattern predicted by prospect theory, suggesting that probability distortion is reflected at the level of the reward encoding process. The degree of nonlinearity reflected in individual subjects' decisions is also correlated with striatal activity across subjects. Our results shed light on the neural mechanisms of reward processing, and have implications for future neuroscientific studies of decision making involving extreme tails of the distribution, where probability weighting provides an explanation for commonly observed behavioral anomalies.
Multivariate injury risk criteria and injury probability scores for fractures to the distal radius.
Burkhart, Timothy A; Andrews, David M; Dunning, Cynthia E
2013-03-15
The purpose of this study was to develop a multivariate distal radius injury risk prediction model that incorporates dynamic loading variables in multiple directions, and interpret the distal radius failure data in order to establish injury probability thresholds. Repeated impacts with increasing intensity were applied to the distal third of eight human cadaveric radius specimens (mean (SD) age=61.9 (9.7)) until injury occurred. Crack (non-propagating damage) and fracture (specimen separated into at least two fragments) injury events were recorded. Best subsets analysis was performed to find the best multivariate injury risk model. Force-only risk models were also determined for comparison. Cumulative distribution functions were developed from the parameters of a Weibull analysis and the forces and risk scores (i.e., values calculated from the injury risk models) from 10% to 90% probability were calculated. According to the adjusted R(2), variance inflation factor and p-values, the model that best predicted the crack event included medial/lateral impulse, Fz load rate, impact velocity and the natural logarithm of Fz (Adj. R(2)=0.698), while the best predictive model of the fracture event included medial/lateral impulse, impact velocity and peak Fz (Adj. R(2)=0.845). The multivariate models predicted injury risk better than both the Fz-only crack (Adj. R(2)=0.551) and fracture (Adj. R(2)=0.293) models. Risk scores of 0.5 and 0.6 corresponded to 10% failure probability for the crack and fracture events, respectively. The inclusion of medial/lateral impulse and impact velocity in both crack and fracture models, and Fz load rate in the crack model, underscores the dynamic nature of these events. This study presents a method capable of developing a set of distal radius fracture prediction models that can be used in the assessment and development of distal radius injury prevention interventions.
NASA Technical Reports Server (NTRS)
Huddleston, Lisa L.; Roeder, William P.; Merceret, Francis J.
2010-01-01
A new technique has been developed to estimate the probability that a nearby cloud-to-ground lightning stroke was within a specified radius of any point of interest. This process uses the bivariate Gaussian distribution of probability density provided by the current lightning location error ellipse for the most likely location of a lightning stroke and integrates it to determine the probability that the stroke is inside any specified radius of any location, even if that location is not centered on or even within the location error ellipse. This technique is adapted from a method of calculating the probability of debris collision with spacecraft. Such a technique is important in spaceport processing activities because it allows engineers to quantify the risk of induced current damage to critical electronics due to nearby lightning strokes. This technique was tested extensively and is now in use by space launch organizations at Kennedy Space Center and Cape Canaveral Air Force station.
NASA Technical Reports Server (NTRS)
Huddleston, Lisa L.; Roeder, William P.; Merceret, Francis J.
2011-01-01
A new technique has been developed to estimate the probability that a nearby cloud to ground lightning stroke was within a specified radius of any point of interest. This process uses the bivariate Gaussian distribution of probability density provided by the current lightning location error ellipse for the most likely location of a lightning stroke and integrates it to determine the probability that the stroke is inside any specified radius of any location, even if that location is not centered on or even with the location error ellipse. This technique is adapted from a method of calculating the probability of debris collision with spacecraft. Such a technique is important in spaceport processing activities because it allows engineers to quantify the risk of induced current damage to critical electronics due to nearby lightning strokes. This technique was tested extensively and is now in use by space launch organizations at Kennedy Space Center and Cape Canaveral Air Force Station. Future applications could include forensic meteorology.
Elliott, John G.; Flynn, Jennifer L.; Bossong, Clifford R.; Char, Stephen J.
2011-01-01
The subwatersheds with the greatest potential postwildfire and postprecipitation hazards are those with both high probabilities of debris-flow occurrence and large estimated volumes of debris-flow material. The high probabilities of postwildfire debris flows, the associated large estimated debris-flow volumes, and the densely populated areas along the creeks and near the outlets of the primary watersheds indicate that Indiana, Pennsylvania, and Spruce Creeks are associated with a relatively high combined debris-flow hazard.
Nielson, Ryan M.; Gray, Brian R.; McDonald, Lyman L.; Heglund, Patricia J.
2011-01-01
Estimation of site occupancy rates when detection probabilities are <1 is well established in wildlife science. Data from multiple visits to a sample of sites are used to estimate detection probabilities and the proportion of sites occupied by focal species. In this article we describe how site occupancy methods can be applied to estimate occupancy rates of plants and other sessile organisms. We illustrate this approach and the pitfalls of ignoring incomplete detection using spatial data for 2 aquatic vascular plants collected under the Upper Mississippi River's Long Term Resource Monitoring Program (LTRMP). Site occupancy models considered include: a naïve model that ignores incomplete detection, a simple site occupancy model assuming a constant occupancy rate and a constant probability of detection across sites, several models that allow site occupancy rates and probabilities of detection to vary with habitat characteristics, and mixture models that allow for unexplained variation in detection probabilities. We used information theoretic methods to rank competing models and bootstrapping to evaluate the goodness-of-fit of the final models. Results of our analysis confirm that ignoring incomplete detection can result in biased estimates of occupancy rates. Estimates of site occupancy rates for 2 aquatic plant species were 19–36% higher compared to naive estimates that ignored probabilities of detection <1. Simulations indicate that final models have little bias when 50 or more sites are sampled, and little gains in precision could be expected for sample sizes >300. We recommend applying site occupancy methods for monitoring presence of aquatic species.
Assessing uncertainty in published risk estimates using ...
Introduction: The National Research Council recommended quantitative evaluation of uncertainty in effect estimates for risk assessment. This analysis considers uncertainty across model forms and model parameterizations with hexavalent chromium [Cr(VI)] and lung cancer mortality as an example. The objective is to characterize model uncertainty by evaluating estimates across published epidemiologic studies of the same cohort.Methods: This analysis was based on 5 studies analyzing a cohort of 2,357 workers employed from 1950-74 in a chromate production plant in Maryland. Cox and Poisson models were the only model forms considered by study authors to assess the effect of Cr(VI) on lung cancer mortality. All models adjusted for smoking and included a 5-year exposure lag, however other latency periods and model covariates such as age and race were considered. Published effect estimates were standardized to the same units and normalized by their variances to produce a standardized metric to compare variability within and between model forms. A total of 5 similarly parameterized analyses were considered across model form, and 16 analyses with alternative parameterizations were considered within model form (10 Cox; 6 Poisson). Results: Across Cox and Poisson model forms, adjusted cumulative exposure coefficients (betas) for 5 similar analyses ranged from 2.47 to 4.33 (mean=2.97, σ2=0.63). Within the 10 Cox models, coefficients ranged from 2.53 to 4.42 (mean=3.29, σ2=0.
Bent, Gardner C.; Archfield, Stacey A.
2002-01-01
A logistic regression equation was developed for estimating the probability of a stream flowing perennially at a specific site in Massachusetts. The equation provides city and town conservation commissions and the Massachusetts Department of Environmental Protection with an additional method for assessing whether streams are perennial or intermittent at a specific site in Massachusetts. This information is needed to assist these environmental agencies, who administer the Commonwealth of Massachusetts Rivers Protection Act of 1996, which establishes a 200-foot-wide protected riverfront area extending along the length of each side of the stream from the mean annual high-water line along each side of perennial streams, with exceptions in some urban areas. The equation was developed by relating the verified perennial or intermittent status of a stream site to selected basin characteristics of naturally flowing streams (no regulation by dams, surface-water withdrawals, ground-water withdrawals, diversion, waste-water discharge, and so forth) in Massachusetts. Stream sites used in the analysis were identified as perennial or intermittent on the basis of review of measured streamflow at sites throughout Massachusetts and on visual observation at sites in the South Coastal Basin, southeastern Massachusetts. Measured or observed zero flow(s) during months of extended drought as defined by the 310 Code of Massachusetts Regulations (CMR) 10.58(2)(a) were not considered when designating the perennial or intermittent status of a stream site. The database used to develop the equation included a total of 305 stream sites (84 intermittent- and 89 perennial-stream sites in the State, and 50 intermittent- and 82 perennial-stream sites in the South Coastal Basin). Stream sites included in the database had drainage areas that ranged from 0.14 to 8.94 square miles in the State and from 0.02 to 7.00 square miles in the South Coastal Basin.Results of the logistic regression analysis
Seismic Risk Assessment and Loss Estimation for Tbilisi City
NASA Astrophysics Data System (ADS)
Tsereteli, Nino; Alania, Victor; Varazanashvili, Otar; Gugeshashvili, Tengiz; Arabidze, Vakhtang; Arevadze, Nika; Tsereteli, Emili; Gaphrindashvili, Giorgi; Gventcadze, Alexander; Goguadze, Nino; Vephkhvadze, Sophio
2013-04-01
The proper assessment of seismic risk is of crucial importance for society protection and city sustainable economic development, as it is the essential part to seismic hazard reduction. Estimation of seismic risk and losses is complicated tasks. There is always knowledge deficiency on real seismic hazard, local site effects, inventory on elements at risk, infrastructure vulnerability, especially for developing countries. Lately great efforts was done in the frame of EMME (earthquake Model for Middle East Region) project, where in the work packages WP1, WP2 , WP3 and WP4 where improved gaps related to seismic hazard assessment and vulnerability analysis. Finely in the frame of work package wp5 "City Scenario" additional work to this direction and detail investigation of local site conditions, active fault (3D) beneath Tbilisi were done. For estimation economic losses the algorithm was prepared taking into account obtained inventory. The long term usage of building is very complex. It relates to the reliability and durability of buildings. The long term usage and durability of a building is determined by the concept of depreciation. Depreciation of an entire building is calculated by summing the products of individual construction unit' depreciation rates and the corresponding value of these units within the building. This method of calculation is based on an assumption that depreciation is proportional to the building's (constructions) useful life. We used this methodology to create a matrix, which provides a way to evaluate the depreciation rates of buildings with different type and construction period and to determine their corresponding value. Finally loss was estimated resulting from shaking 10%, 5% and 2% exceedance probability in 50 years. Loss resulting from scenario earthquake (earthquake with possible maximum magnitude) also where estimated.
Over, Thomas; Saito, Riki J.; Veilleux, Andrea; Sharpe, Jennifer B.; Soong, David T.; Ishii, Audrey
2016-06-28
This report provides two sets of equations for estimating peak discharge quantiles at annual exceedance probabilities (AEPs) of 0.50, 0.20, 0.10, 0.04, 0.02, 0.01, 0.005, and 0.002 (recurrence intervals of 2, 5, 10, 25, 50, 100, 200, and 500 years, respectively) for watersheds in Illinois based on annual maximum peak discharge data from 117 watersheds in and near northeastern Illinois. One set of equations was developed through a temporal analysis with a two-step least squares-quantile regression technique that measures the average effect of changes in the urbanization of the watersheds used in the study. The resulting equations can be used to adjust rural peak discharge quantiles for the effect of urbanization, and in this study the equations also were used to adjust the annual maximum peak discharges from the study watersheds to 2010 urbanization conditions.The other set of equations was developed by a spatial analysis. This analysis used generalized least-squares regression to fit the peak discharge quantiles computed from the urbanization-adjusted annual maximum peak discharges from the study watersheds to drainage-basin characteristics. The peak discharge quantiles were computed by using the Expected Moments Algorithm following the removal of potentially influential low floods defined by a multiple Grubbs-Beck test. To improve the quantile estimates, generalized skew coefficients were obtained from a newly developed regional skew model in which the skew increases with the urbanized land use fraction. The drainage-basin characteristics used as explanatory variables in the spatial analysis include drainage area, the fraction of developed land, the fraction of land with poorly drained soils or likely water, and the basin slope estimated as the ratio of the basin relief to basin perimeter.This report also provides the following: (1) examples to illustrate the use of the spatial and urbanization-adjustment equations for estimating peak discharge quantiles at
IMPROVED RISK ESTIMATES FOR CARBON TETRACHLORIDE
Benson, Janet M.; Springer, David L.
1999-12-31
Carbon tetrachloride has been used extensively within the DOE nuclear weapons facilities. Rocky Flats was formerly the largest volume consumer of CCl4 in the United States using 5000 gallons in 1977 alone (Ripple, 1992). At the Hanford site, several hundred thousand gallons of CCl4 were discharged between 1955 and 1973 into underground cribs for storage. Levels of CCl4 in groundwater at highly contaminated sites at the Hanford facility have exceeded 8 the drinking water standard of 5 ppb by several orders of magnitude (Illman, 1993). High levels of CCl4 at these facilities represent a potential health hazard for workers conducting cleanup operations and for surrounding communities. The level of CCl4 cleanup required at these sites and associated costs are driven by current human health risk estimates, which assume that CCl4 is a genotoxic carcinogen. The overall purpose of these studies was to improve the scientific basis for assessing the health risk associated with human exposure to CCl4. Specific research objectives of this project were to: (1) compare the rates of CCl4 metabolism by rats, mice and hamsters in vivo and extrapolate those rates to man based on parallel studies on the metabolism of CCl4 by rat, mouse, hamster and human hepatic microsomes in vitro; (2) using hepatic microsome preparations, determine the role of specific cytochrome P450 isoforms in CCl4-mediated toxicity and the effects of repeated inhalation and ingestion of CCl4 on these isoforms; and (3) evaluate the toxicokinetics of inhaled CCl4 in rats, mice and hamsters. This information has been used to improve the physiologically based pharmacokinetic (PBPK) model for CCl4 originally developed by Paustenbach et al. (1988) and more recently revised by Thrall and Kenny (1996). Another major objective of the project was to provide scientific evidence that CCl4, like chloroform, is a hepatocarcinogen only when exposure results in cell damage, cell killing and regenerative proliferation. In
Haber, M.; An, Q.; Foppa, I. M.; Shay, D. K.; Ferdinands, J. M.; Orenstein, W. A.
2014-01-01
Summary As influenza vaccination is now widely recommended, randomized clinical trials are no longer ethical in many populations. Therefore, observational studies on patients seeking medical care for acute respiratory illnesses (ARI) are a popular option for estimating influenza vaccine effectiveness (VE). We developed a probability model for evaluating and comparing bias and precision of estimates of VE against symptomatic influenza from two commonly-used case-control study designs: the test-negative design and the traditional case-control design. We show that when vaccination does not affect the probability of developing non-influenza ARI then VE estimates from test-negative design studies are unbiased even if vaccinees and non-vaccinees have different probabilities of seeking medical care against ARI, as long as the ratio of these probabilities is the same for illnesses resulting from influenza and non-influenza infections. Our numerical results suggest that in general, estimates from the test-negative design have smaller bias compared to estimates from the traditional case-control design as long as the probability of non-influenza ARI is similar among vaccinated and unvaccinated individuals. We did not find consistent differences between the standard errors of the estimates from the two study designs. PMID:25147970
Cook, D A
2006-04-01
Models that estimate the probability of death of intensive care unit patients can be used to stratify patients according to the severity of their condition and to control for casemix and severity of illness. These models have been used for risk adjustment in quality monitoring, administration, management and research and as an aid to clinical decision making. Models such as the Mortality Prediction Model family, SAPS II, APACHE II, APACHE III and the organ system failure models provide estimates of the probability of in-hospital death of ICU patients. This review examines methods to assess the performance of these models. The key attributes of a model are discrimination (the accuracy of the ranking in order of probability of death) and calibration (the extent to which the model's prediction of probability of death reflects the true risk of death). These attributes should be assessed in existing models that predict the probability of patient mortality, and in any subsequent model that is developed for the purposes of estimating these probabilities. The literature contains a range of approaches for assessment which are reviewed and a survey of the methodologies used in studies of intensive care mortality models is presented. The systematic approach used by Standards for Reporting Diagnostic Accuracy provides a framework to incorporate these theoretical considerations of model assessment and recommendations are made for evaluation and presentation of the performance of models that estimate the probability of death of intensive care patients.
Estimation of the Probable Maximum Flood for a Small Lowland River in Poland
NASA Astrophysics Data System (ADS)
Banasik, K.; Hejduk, L.
2009-04-01
The planning, designe and use of hydrotechnical structures often requires the assesment of maximu flood potentials. The most common term applied to this upper limit of flooding is the probable maximum flood (PMF). The PMP/UH (probable maximum precipitation/unit hydrograph) method has been used in the study to predict PMF from a small agricultural lowland river basin of Zagozdzonka (left tributary of Vistula river) in Poland. The river basin, located about 100 km south of Warsaw, with an area - upstream the gauge of Plachty - of 82 km2, has been investigated by Department of Water Engineering and Environmenal Restoration of Warsaw University of Life Sciences - SGGW since 1962. Over 40-year flow record was used in previous investigation for predicting T-year flood discharge (Banasik et al., 2003). The objective here was to estimate the PMF using the PMP/UH method and to compare the results with the 100-year flood. A new relation of depth-duration curve of PMP for the local climatic condition has been developed based on Polish maximum observed rainfall data (Ozga-Zielinska & Ozga-Zielinski, 2003). Exponential formula, with the value of exponent of 0.47, i.e. close to the exponent in formula for world PMP and also in the formula of PMP for Great Britain (Wilson, 1993), gives the rainfall depth about 40% lower than the Wilson's one. The effective rainfall (runoff volume) has been estimated from the PMP of various duration using the CN-method (USDA-SCS, 1986). The CN value as well as parameters of the IUH model (Nash, 1957) have been established from the 27 rainfall-runoff events, recorded in the river basin in the period 1980-2004. Varibility of the parameter values with the size of the events will be discussed in the paper. The results of the analyse have shown that the peak discharge of the PMF is 4.5 times larger then 100-year flood, and volume ratio of the respective direct hydrographs caused by rainfall events of critical duration is 4.0. References 1.Banasik K
Estimation of the Probable Maximum Flood for a Small Lowland River in Poland
NASA Astrophysics Data System (ADS)
Banasik, K.; Hejduk, L.
2009-04-01
The planning, designe and use of hydrotechnical structures often requires the assesment of maximu flood potentials. The most common term applied to this upper limit of flooding is the probable maximum flood (PMF). The PMP/UH (probable maximum precipitation/unit hydrograph) method has been used in the study to predict PMF from a small agricultural lowland river basin of Zagozdzonka (left tributary of Vistula river) in Poland. The river basin, located about 100 km south of Warsaw, with an area - upstream the gauge of Plachty - of 82 km2, has been investigated by Department of Water Engineering and Environmenal Restoration of Warsaw University of Life Sciences - SGGW since 1962. Over 40-year flow record was used in previous investigation for predicting T-year flood discharge (Banasik et al., 2003). The objective here was to estimate the PMF using the PMP/UH method and to compare the results with the 100-year flood. A new relation of depth-duration curve of PMP for the local climatic condition has been developed based on Polish maximum observed rainfall data (Ozga-Zielinska & Ozga-Zielinski, 2003). Exponential formula, with the value of exponent of 0.47, i.e. close to the exponent in formula for world PMP and also in the formula of PMP for Great Britain (Wilson, 1993), gives the rainfall depth about 40% lower than the Wilson's one. The effective rainfall (runoff volume) has been estimated from the PMP of various duration using the CN-method (USDA-SCS, 1986). The CN value as well as parameters of the IUH model (Nash, 1957) have been established from the 27 rainfall-runoff events, recorded in the river basin in the period 1980-2004. Varibility of the parameter values with the size of the events will be discussed in the paper. The results of the analyse have shown that the peak discharge of the PMF is 4.5 times larger then 100-year flood, and volume ratio of the respective direct hydrographs caused by rainfall events of critical duration is 4.0. References 1.Banasik K
Das, Jayajit; Mukherjee, Sayak; Hodge, Susan E
2015-07-01
A common statistical situation concerns inferring an unknown distribution Q(x) from a known distribution P(y), where X (dimension n), and Y (dimension m) have a known functional relationship. Most commonly, n ≤ m, and the task is relatively straightforward for well-defined functional relationships. For example, if Y1 and Y2 are independent random variables, each uniform on [0, 1], one can determine the distribution of X = Y1 + Y2; here m = 2 and n = 1. However, biological and physical situations can arise where n > m and the functional relation Y→X is non-unique. In general, in the absence of additional information, there is no unique solution to Q in those cases. Nevertheless, one may still want to draw some inferences about Q. To this end, we propose a novel maximum entropy (MaxEnt) approach that estimates Q(x) based only on the available data, namely, P(y). The method has the additional advantage that one does not need to explicitly calculate the Lagrange multipliers. In this paper we develop the approach, for both discrete and continuous probability distributions, and demonstrate its validity. We give an intuitive justification as well, and we illustrate with examples.
Dictionary-based probability density function estimation for high-resolution SAR data
NASA Astrophysics Data System (ADS)
Krylov, Vladimir; Moser, Gabriele; Serpico, Sebastiano B.; Zerubia, Josiane
2009-02-01
In the context of remotely sensed data analysis, a crucial problem is represented by the need to develop accurate models for the statistics of pixel intensities. In this work, we develop a parametric finite mixture model for the statistics of pixel intensities in high resolution synthetic aperture radar (SAR) images. This method is an extension of previously existing method for lower resolution images. The method integrates the stochastic expectation maximization (SEM) scheme and the method of log-cumulants (MoLC) with an automatic technique to select, for each mixture component, an optimal parametric model taken from a predefined dictionary of parametric probability density functions (pdf). The proposed dictionary consists of eight state-of-the-art SAR-specific pdfs: Nakagami, log-normal, generalized Gaussian Rayleigh, Heavy-tailed Rayleigh, Weibull, K-root, Fisher and generalized Gamma. The designed scheme is endowed with the novel initialization procedure and the algorithm to automatically estimate the optimal number of mixture components. The experimental results with a set of several high resolution COSMO-SkyMed images demonstrate the high accuracy of the designed algorithm, both from the viewpoint of a visual comparison of the histograms, and from the viewpoint of quantitive accuracy measures such as correlation coefficient (above 99,5%). The method proves to be effective on all the considered images, remaining accurate for multimodal and highly heterogeneous scenes.
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.
NASA Astrophysics Data System (ADS)
Lussana, C.
2013-04-01
The presented work focuses on the investigation of gridded daily minimum (TN) and maximum (TX) temperature probability density functions (PDFs) with the intent of both characterising a region and detecting extreme values. The empirical PDFs estimation procedure has been realised using the most recent years of gridded temperature analysis fields available at ARPA Lombardia, in Northern Italy. The spatial interpolation is based on an implementation of Optimal Interpolation using observations from a dense surface network of automated weather stations. An effort has been made to identify both the time period and the spatial areas with a stable data density otherwise the elaboration could be influenced by the unsettled station distribution. The PDF used in this study is based on the Gaussian distribution, nevertheless it is designed to have an asymmetrical (skewed) shape in order to enable distinction between warming and cooling events. Once properly defined the occurrence of extreme events, it is possible to straightforwardly deliver to the users the information on a local-scale in a concise way, such as: TX extremely cold/hot or TN extremely cold/hot.
Large, Matthew
2013-12-01
Probability theory is at the base of modern concepts of risk assessment in mental health. The aim of the current paper is to review the key developments in the early history of probability theory in order to enrich our understanding of current risk assessment practices.
Nilsson, Håkan; Juslin, Peter; Winman, Anders
2016-01-01
Costello and Watts (2014) present a model assuming that people's knowledge of probabilities adheres to probability theory, but that their probability judgments are perturbed by a random noise in the retrieval from memory. Predictions for the relationships between probability judgments for constituent events and their disjunctions and conjunctions, as well as for sums of such judgments were derived from probability theory. Costello and Watts (2014) report behavioral data showing that subjective probability judgments accord with these predictions. Based on the finding that subjective probability judgments follow probability theory, Costello and Watts (2014) conclude that the results imply that people's probability judgments embody the rules of probability theory and thereby refute theories of heuristic processing. Here, we demonstrate the invalidity of this conclusion by showing that all of the tested predictions follow straightforwardly from an account assuming heuristic probability integration (Nilsson, Winman, Juslin, & Hansson, 2009). We end with a discussion of a number of previous findings that harmonize very poorly with the predictions by the model suggested by Costello and Watts (2014).
The Human Bathtub: Safety and Risk Predictions Including the Dynamic Probability of Operator Errors
Duffey, Romney B.; Saull, John W.
2006-07-01
Reactor safety and risk are dominated by the potential and major contribution for human error in the design, operation, control, management, regulation and maintenance of the plant, and hence to all accidents. Given the possibility of accidents and errors, now we need to determine the outcome (error) probability, or the chance of failure. Conventionally, reliability engineering is associated with the failure rate of components, or systems, or mechanisms, not of human beings in and interacting with a technological system. The probability of failure requires a prior knowledge of the total number of outcomes, which for any predictive purposes we do not know or have. Analysis of failure rates due to human error and the rate of learning allow a new determination of the dynamic human error rate in technological systems, consistent with and derived from the available world data. The basis for the analysis is the 'learning hypothesis' that humans learn from experience, and consequently the accumulated experience defines the failure rate. A new 'best' equation has been derived for the human error, outcome or failure rate, which allows for calculation and prediction of the probability of human error. We also provide comparisons to the empirical Weibull parameter fitting used in and by conventional reliability engineering and probabilistic safety analysis methods. These new analyses show that arbitrary Weibull fitting parameters and typical empirical hazard function techniques cannot be used to predict the dynamics of human errors and outcomes in the presence of learning. Comparisons of these new insights show agreement with human error data from the world's commercial airlines, the two shuttle failures, and from nuclear plant operator actions and transient control behavior observed in transients in both plants and simulators. The results demonstrate that the human error probability (HEP) is dynamic, and that it may be predicted using the learning hypothesis and the minimum
Estimation of health risks from radiation exposures
Randolph, M.L.
1983-08-01
An informal presentation is given of the cancer and genetic risks from exposures to ionizing radiations. The risks from plausible radiation exposures are shown to be comparable to other commonly encountered risks.
Probability-Weighted Ensembles of U.S. County-Level Climate Projections for Climate Risk Analysis
NASA Astrophysics Data System (ADS)
Rasmussen, D. J.; Meinshausen, Malte; Kopp, Robert E.
2016-10-01
Quantitative assessment of climate change risk requires a method for constructing probabilistic time series of changes in physical climate parameters. Here, we develop two such methods, Surrogate/Model Mixed Ensemble (SMME) and Monte Carlo Pattern/Residual (MCPR), and apply them to construct joint probability density functions (PDFs) of temperature and precipitation change over the 21st century for every county in the United States. Both methods produce $likely$ (67% probability) temperature and precipitation projections consistent with the Intergovernmental Panel on Climate Change's interpretation of an equal-weighted Coupled Model Intercomparison Project 5 (CMIP5) ensemble, but also provide full PDFs that include tail estimates. For example, both methods indicate that, under representative concentration pathway (RCP) 8.5, there is a 5% chance that the contiguous United States could warm by at least 8$^\\circ$C. Variance decomposition of SMME and MCPR projections indicate that background variability dominates uncertainty in the early 21st century, while forcing-driven changes emerge in the second half of the 21st century. By separating CMIP5 projections into unforced and forced components using linear regression, these methods generate estimates of unforced variability from existing CMIP5 projections without requiring the computationally expensive use of multiple realizations of a single GCM.
NASA Technical Reports Server (NTRS)
Frigm, Ryan C.; Hejduk, Matthew D.; Johnson, Lauren C.; Plakalovic, Dragan
2015-01-01
On-orbit collision risk is becoming an increasing mission risk to all operational satellites in Earth orbit. Managing this risk can be disruptive to mission and operations, present challenges for decision-makers, and is time-consuming for all parties involved. With the planned capability improvements to detecting and tracking smaller orbital debris and capacity improvements to routinely predict on-orbit conjunctions, this mission risk will continue to grow in terms of likelihood and effort. It is very real possibility that the future space environment will not allow collision risk management and mission operations to be conducted in the same manner as it is today. This paper presents the concept of a finite conjunction assessment-one where each discrete conjunction is not treated separately but, rather, as a continuous event that must be managed concurrently. The paper also introduces the Total Probability of Collision as an analogous metric for finite conjunction assessment operations and provides several options for its usage in a Concept of Operations.
NASA Astrophysics Data System (ADS)
Zhong, H.; van Overloop, P.-J.; van Gelder, P. H. A. J. M.
2013-07-01
The Lower Rhine Delta, a transitional area between the River Rhine and Meuse and the North Sea, is at risk of flooding induced by infrequent events of a storm surge or upstream flooding, or by more infrequent events of a combination of both. A joint probability analysis of the astronomical tide, the wind induced storm surge, the Rhine flow and the Meuse flow at the boundaries is established in order to produce the joint probability distribution of potential flood events. Three individual joint probability distributions are established corresponding to three potential flooding causes: storm surges and normal Rhine discharges, normal sea levels and high Rhine discharges, and storm surges and high Rhine discharges. For each category, its corresponding joint probability distribution is applied, in order to stochastically simulate a large number of scenarios. These scenarios can be used as inputs to a deterministic 1-D hydrodynamic model in order to estimate the high water level frequency curves at the transitional locations. The results present the exceedance probability of the present design water level for the economically important cities of Rotterdam and Dordrecht. The calculated exceedance probability is evaluated and compared to the governmental norm. Moreover, the impact of climate change on the high water level frequency curves is quantified for the year 2050 in order to assist in decisions regarding the adaptation of the operational water management system and the flood defense system.
NASA Technical Reports Server (NTRS)
Wiegmann, Douglas A.a
2005-01-01
The NASA Aviation Safety Program (AvSP) has defined several products that will potentially modify airline and/or ATC operations, enhance aircraft systems, and improve the identification of potential hazardous situations within the National Airspace System (NAS). Consequently, there is a need to develop methods for evaluating the potential safety benefit of each of these intervention products so that resources can be effectively invested to produce the judgments to develop Bayesian Belief Networks (BBN's) that model the potential impact that specific interventions may have. Specifically, the present report summarizes methodologies for improving the elicitation of probability estimates during expert evaluations of AvSP products for use in BBN's. The work involved joint efforts between Professor James Luxhoj from Rutgers University and researchers at the University of Illinois. The Rutgers' project to develop BBN's received funding by NASA entitled "Probabilistic Decision Support for Evaluating Technology Insertion and Assessing Aviation Safety System Risk." The proposed project was funded separately but supported the existing Rutgers' program.
Uncertainty of Calculated Risk Estimates for Secondary Malignancies After Radiotherapy
Kry, Stephen F. . E-mail: sfkry@mdanderson.org; Followill, David; White, R. Allen; Stovall, Marilyn; Kuban, Deborah A.; Salehpour, Mohammad
2007-07-15
Purpose: The significance of risk estimates for fatal secondary malignancies caused by out-of-field radiation exposure remains unresolved because the uncertainty in calculated risk estimates has not been established. This work examines the uncertainty in absolute risk estimates and in the ratio of risk estimates between different treatment modalities. Methods and Materials: Clinically reasonable out-of-field doses and calculated risk estimates were taken from the literature for several prostate treatment modalities, including intensity-modulated radiotherapy (IMRT), and were recalculated using the most recent risk model. The uncertainties in this risk model and uncertainties in the linearity of the dose-response model were considered in generating 90% confidence intervals for the uncertainty in the absolute risk estimates and in the ratio of the risk estimates. Results: The absolute risk estimates of fatal secondary malignancy were associated with very large uncertainties, which precluded distinctions between the risks associated with the different treatment modalities considered. However, a much smaller confidence interval exists for the ratio of risk estimates, and this ratio between different treatment modalities may be statistically significant when there is an effective dose equivalent difference of at least 50%. Such a difference may exist between clinically reasonable treatment options, including 6-MV IMRT versus 18-MV IMRT for prostate therapy. Conclusion: The ratio of the risk between different treatment modalities may be significantly different. Consequently risk models and associated risk estimates may be useful and meaningful for evaluating different treatment options. The calculated risk of secondary malignancy should be considered in the selection of an optimal treatment plan.
Probable Health Risks Due to Exposure to Outdoor PM2.5 in India
NASA Astrophysics Data System (ADS)
Dey, S.; Chowdhury, S.
2014-12-01
Particulate matter of size <2.5 μm (commonly referred to as PM2.5) is considered to be the best indicator of health risks due to exposure to particulate pollution. Unlike the decreasing trends in the developed countries, aerosol loading continues to increase over the Indian subcontinent in the recent past, exposing ~1.6 billion population at risk. Lack of direct measurements prompted us to utilize satellite data in establishing a robust long-term database of surface PM2.5 at high spatial resolution. The hybrid approach utilizes a chemical transport model to constrain the relation between columnar aerosol optical depth (AOD) and surface PM2.5 and establish mean monthly conversion factor. Satellite-derived daily AODs for the period 2000-2012 are then converted to PM2.5 using the conversion factors. The dataset (after validation against coincident in-situ measurements and bias-correction) was used to carry out the exposure assessment. 51% of the population is exposed to PM2.5 concentration exceeding WHO air quality interim target-3 threshold (35 μg m-3). The health impacts are categorized in terms of four diseases - cardio ortho-pulmonary disease (COPD), stroke, ischemic heart disease (IHD) and lung cancer (LC). In absence of any region-specific cohort study, published studies are consulted to estimate risk. The risks relative to the background concentration of 10 μg m-3 are estimated by logarithmic fitting of the individual cohort studies against the corresponding PM2.5 concentration. This approach considers multiple (>100) cohort studies across a wide variety of adult population from various socio-economic backgrounds. Therefore, the calculated risks are considered to be better estimates in relative to any one particular type of risk function model (e.g. linear 50 or linear 70 or exponential). The risk values are used to calculate the additional mortality due to exposure to PM2.5 in each of the administrative districts in India to identify the vulnerable regions
Timonina, Anna; Hochrainer-Stigler, Stefan; Pflug, Georg; Jongman, Brenden; Rojas, Rodrigo
2015-11-01
Losses due to natural hazard events can be extraordinarily high and difficult to cope with. Therefore, there is considerable interest to estimate the potential impact of current and future extreme events at all scales in as much detail as possible. As hazards typically spread over wider areas, risk assessment must take into account interrelations between regions. Neglecting such interdependencies can lead to a severe underestimation of potential losses, especially for extreme events. This underestimation of extreme risk can lead to the failure of riskmanagement strategies when they are most needed, namely, in times of unprecedented events. In this article, we suggest a methodology to incorporate such interdependencies in risk via the use of copulas. We demonstrate that by coupling losses, dependencies can be incorporated in risk analysis, avoiding the underestimation of risk. Based on maximum discharge data of river basins and stream networks, we present and discuss different ways to couple loss distributions of basins while explicitly incorporating tail dependencies. We distinguish between coupling methods that require river structure data for the analysis and those that do not. For the later approach we propose a minimax algorithm to choose coupled basin pairs so that the underestimation of risk is avoided and the use of river structure data is not needed. The proposed methodology is especially useful for large-scale analysis and we motivate and apply our method using the case of Romania. The approach can be easily extended to other countries and natural hazards.
How are flood risk estimates affected by the choice of return-periods?
NASA Astrophysics Data System (ADS)
Ward, P. J.; Aerts, J. C. J. H.; De Moel, H.; Poussin, J. K.
2012-04-01
Flood management is more and more adopting a risk based approach, whereby flood risk is the product of the probability and consequences of flooding. One of the most common approaches in flood risk assessment is to estimate the damage that would occur for floods of several exceedance probabilities (or return periods), to plot these on an exceedance probability-loss curve (risk curve) and to estimate risk as the area under the curve. However, there is little insight into how the selection of the return-periods (which ones and how many) used to calculate risk actually affects the final risk calculation. To gain such insights, we developed and validated an inundation model capable of rapidly simulating inundation extent and depth, and dynamically coupled this to an existing damage model. The method was applied to a section of the River Meuse in the southeast of the Netherlands. Firstly, we estimated risk based on a risk curve using yearly return periods from 2 to 10 000 yr (€ 34 million p.a.). We found that the overall risk is greatly affected by the number of return periods used to construct the risk curve, with over-estimations of annual risk between 33% and 100% when only three return periods are used. Also, the final risk estimate is greatly dependent on the minimum and maximum return periods (and their associated damages) used in the construction of the risk curve. In addition, binary assumptions on dike failure can have a large effect (a factor two difference) on risk estimates. The results suggest that more research is needed to develop relatively simple inundation models that can be used to produce large numbers of inundation maps, complementary to more complex 2D-3D hydrodynamic models. We then used the insights and models described above to assess the relative change in risk between current conditions and several scenarios of land use and climate change. For the case study region, we found that future land use change has a larger impact than future climate
Probability of fracture and life extension estimate of the high-flux isotope reactor vessel
Chang, S.J.
1998-08-01
The state of the vessel steel embrittlement as a result of neutron irradiation can be measured by its increase in ductile-brittle transition temperature (DBTT) for fracture, often denoted by RT{sub NDT} for carbon steel. This transition temperature can be calibrated by the drop-weight test and, sometimes, by the Charpy impact test. The life extension for the high-flux isotope reactor (HFIR) vessel is calculated by using the method of fracture mechanics that is incorporated with the effect of the DBTT change. The failure probability of the HFIR vessel is limited as the life of the vessel by the reactor core melt probability of 10{sup {minus}4}. The operating safety of the reactor is ensured by periodic hydrostatic pressure test (hydrotest). The hydrotest is performed in order to determine a safe vessel static pressure. The fracture probability as a result of the hydrostatic pressure test is calculated and is used to determine the life of the vessel. Failure to perform hydrotest imposes the limit on the life of the vessel. The conventional method of fracture probability calculations such as that used by the NRC-sponsored PRAISE CODE and the FAVOR CODE developed in this Laboratory are based on the Monte Carlo simulation. Heavy computations are required. An alternative method of fracture probability calculation by direct probability integration is developed in this paper. The present approach offers simple and expedient ways to obtain numerical results without losing any generality. In this paper, numerical results on (1) the probability of vessel fracture, (2) the hydrotest time interval, and (3) the hydrotest pressure as a result of the DBTT increase are obtained.
NASA Technical Reports Server (NTRS)
Watson, Clifford
2010-01-01
Traditional hazard analysis techniques utilize a two-dimensional representation of the results determined by relative likelihood and severity of the residual risk. These matrices present a quick-look at the Likelihood (Y-axis) and Severity (X-axis) of the probable outcome of a hazardous event. A three-dimensional method, described herein, utilizes the traditional X and Y axes, while adding a new, third dimension, shown as the Z-axis, and referred to as the Level of Control. The elements of the Z-axis are modifications of the Hazard Elimination and Control steps (also known as the Hazard Reduction Precedence Sequence). These steps are: 1. Eliminate risk through design. 2. Substitute less risky materials for more hazardous materials. 3. Install safety devices. 4. Install caution and warning devices. 5. Develop administrative controls (to include special procedures and training.) 6. Provide protective clothing and equipment. When added to the twodimensional models, the level of control adds a visual representation of the risk associated with the hazardous condition, creating a tall-pole for the least-well-controlled failure while establishing the relative likelihood and severity of all causes and effects for an identified hazard. Computer modeling of the analytical results, using spreadsheets and threedimensional charting gives a visual confirmation of the relationship between causes and their controls
NASA Technical Reports Server (NTRS)
Watson, Clifford C.
2011-01-01
Traditional hazard analysis techniques utilize a two-dimensional representation of the results determined by relative likelihood and severity of the residual risk. These matrices present a quick-look at the Likelihood (Y-axis) and Severity (X-axis) of the probable outcome of a hazardous event. A three-dimensional method, described herein, utilizes the traditional X and Y axes, while adding a new, third dimension, shown as the Z-axis, and referred to as the Level of Control. The elements of the Z-axis are modifications of the Hazard Elimination and Control steps (also known as the Hazard Reduction Precedence Sequence). These steps are: 1. Eliminate risk through design. 2. Substitute less risky materials for more hazardous materials. 3. Install safety devices. 4. Install caution and warning devices. 5. Develop administrative controls (to include special procedures and training.) 6. Provide protective clothing and equipment. When added to the two-dimensional models, the level of control adds a visual representation of the risk associated with the hazardous condition, creating a tall-pole for the least-well-controlled failure while establishing the relative likelihood and severity of all causes and effects for an identified hazard. Computer modeling of the analytical results, using spreadsheets and three-dimensional charting gives a visual confirmation of the relationship between causes and their controls.
Sawosz, P; Kacprzak, M; Weigl, W; Borowska-Solonynko, A; Krajewski, P; Zolek, N; Ciszek, B; Maniewski, R; Liebert, A
2012-12-07
A time-gated intensified CCD camera was applied for time-resolved imaging of light penetrating in an optically turbid medium. Spatial distributions of light penetration probability in the plane perpendicular to the axes of the source and the detector were determined at different source positions. Furthermore, visiting probability profiles of diffuse reflectance measurement were obtained by the convolution of the light penetration distributions recorded at different source positions. Experiments were carried out on homogeneous phantoms, more realistic two-layered tissue phantoms based on the human skull filled with Intralipid-ink solution and on cadavers. It was noted that the photons visiting probability profiles depend strongly on the source-detector separation, the delay between the laser pulse and the photons collection window and the complex tissue composition of the human head.
NASA Astrophysics Data System (ADS)
Sawosz, P.; Kacprzak, M.; Weigl, W.; Borowska-Solonynko, A.; Krajewski, P.; Zolek, N.; Ciszek, B.; Maniewski, R.; Liebert, A.
2012-12-01
A time-gated intensified CCD camera was applied for time-resolved imaging of light penetrating in an optically turbid medium. Spatial distributions of light penetration probability in the plane perpendicular to the axes of the source and the detector were determined at different source positions. Furthermore, visiting probability profiles of diffuse reflectance measurement were obtained by the convolution of the light penetration distributions recorded at different source positions. Experiments were carried out on homogeneous phantoms, more realistic two-layered tissue phantoms based on the human skull filled with Intralipid-ink solution and on cadavers. It was noted that the photons visiting probability profiles depend strongly on the source-detector separation, the delay between the laser pulse and the photons collection window and the complex tissue composition of the human head.
A model selection algorithm for a posteriori probability estimation with neural networks.
Arribas, Juan Ignacio; Cid-Sueiro, Jesús
2005-07-01
This paper proposes a novel algorithm to jointly determine the structure and the parameters of a posteriori probability model based on neural networks (NNs). It makes use of well-known ideas of pruning, splitting, and merging neural components and takes advantage of the probabilistic interpretation of these components. The algorithm, so called a posteriori probability model selection (PPMS), is applied to an NN architecture called the generalized softmax perceptron (GSP) whose outputs can be understood as probabilities although results shown can be extended to more general network architectures. Learning rules are derived from the application of the expectation-maximization algorithm to the GSP-PPMS structure. Simulation results show the advantages of the proposed algorithm with respect to other schemes.
Sample Size Determination for Estimation of Sensor Detection Probabilities Based on a Test Variable
2007-06-01
interest. 15. NUMBER OF PAGES 121 14. SUBJECT TERMS Sample Size, Binomial Proportion, Confidence Interval , Coverage Probability, Experimental...THE STUDY ..........................5 II. LITERATURE REVIEW .......................................7 A. CONFIDENCE INTERVAL METHODS FOR THE...BINOMIAL PROPORTION .........................................7 1. The Wald Confidence Interval ..................7 2. The Wilson Score Confidence Interval .........13
Predicting Human Performance. I. Estimating the Probability of Visual Detection. Final Report.
ERIC Educational Resources Information Center
Teichner, Warren H.; Krebs, Marjorie J.
This review is one in a series intended to develop methods which maximize the use of the existing scientific literature as a basis for predicting human performance. It is concerned with sensory performance in target detection, defined in terms of the "probability of detection" of a flash of light. Two conditions of detection are…
Voon, Valerie; Morris, Laurel S; Irvine, Michael A; Ruck, Christian; Worbe, Yulia; Derbyshire, Katherine; Rankov, Vladan; Schreiber, Liana RN; Odlaug, Brian L; Harrison, Neil A; Wood, Jonathan; Robbins, Trevor W; Bullmore, Edward T; Grant, Jon E
2015-01-01
Pathological behaviors toward drugs and food rewards have underlying commonalities. Risk-taking has a fourfold pattern varying as a function of probability and valence leading to the nonlinearity of probability weighting with overweighting of small probabilities and underweighting of large probabilities. Here we assess these influences on risk-taking in patients with pathological behaviors toward drug and food rewards and examine structural neural correlates of nonlinearity of probability weighting in healthy volunteers. In the anticipation of rewards, subjects with binge eating disorder show greater risk-taking, similar to substance-use disorders. Methamphetamine-dependent subjects had greater nonlinearity of probability weighting along with impaired subjective discrimination of probability and reward magnitude. Ex-smokers also had lower risk-taking to rewards compared with non-smokers. In the anticipation of losses, obesity without binge eating had a similar pattern to other substance-use disorders. Obese subjects with binge eating also have impaired discrimination of subjective value similar to that of the methamphetamine-dependent subjects. Nonlinearity of probability weighting was associated with lower gray matter volume in dorsolateral and ventromedial prefrontal cortex and orbitofrontal cortex in healthy volunteers. Our findings support a distinct subtype of binge eating disorder in obesity with similarities in risk-taking in the reward domain to substance use disorders. The results dovetail with the current approach of defining mechanistically based dimensional approaches rather than categorical approaches to psychiatric disorders. The relationship to risk probability and valence may underlie the propensity toward pathological behaviors toward different types of rewards. PMID:25270821
Voon, Valerie; Morris, Laurel S; Irvine, Michael A; Ruck, Christian; Worbe, Yulia; Derbyshire, Katherine; Rankov, Vladan; Schreiber, Liana Rn; Odlaug, Brian L; Harrison, Neil A; Wood, Jonathan; Robbins, Trevor W; Bullmore, Edward T; Grant, Jon E
2015-03-01
Pathological behaviors toward drugs and food rewards have underlying commonalities. Risk-taking has a fourfold pattern varying as a function of probability and valence leading to the nonlinearity of probability weighting with overweighting of small probabilities and underweighting of large probabilities. Here we assess these influences on risk-taking in patients with pathological behaviors toward drug and food rewards and examine structural neural correlates of nonlinearity of probability weighting in healthy volunteers. In the anticipation of rewards, subjects with binge eating disorder show greater risk-taking, similar to substance-use disorders. Methamphetamine-dependent subjects had greater nonlinearity of probability weighting along with impaired subjective discrimination of probability and reward magnitude. Ex-smokers also had lower risk-taking to rewards compared with non-smokers. In the anticipation of losses, obesity without binge eating had a similar pattern to other substance-use disorders. Obese subjects with binge eating also have impaired discrimination of subjective value similar to that of the methamphetamine-dependent subjects. Nonlinearity of probability weighting was associated with lower gray matter volume in dorsolateral and ventromedial prefrontal cortex and orbitofrontal cortex in healthy volunteers. Our findings support a distinct subtype of binge eating disorder in obesity with similarities in risk-taking in the reward domain to substance use disorders. The results dovetail with the current approach of defining mechanistically based dimensional approaches rather than categorical approaches to psychiatric disorders. The relationship to risk probability and valence may underlie the propensity toward pathological behaviors toward different types of rewards.
Multiple primary tumours: incidence estimation in the presence of competing risks
Rosso, Stefano; Terracini, Lea; Ricceri, Fulvio; Zanetti, Roberto
2009-01-01
Background Estimating the risk of developing subsequent primary tumours in a population is difficult since the occurrence probability is conditioned to the survival probability. Methods We proposed to apply Markov models studying the transition intensities from first to second tumour with the Aalen-Johansen (AJ) estimators, as usually done in competing risk models. In a simulation study we applied the proposed method in different settings with constant or varying underlying intensities and applying age standardisation. In addition, we illustrated the method with data on breast cancer from the Piedmont Cancer Registry. Results The simulation study showed that the person-years approach led to a sensibly wider bias than the AJ estimators. The largest bias was observed assuming constantly increasing incidence rates. However, this situation is rather uncommon dealing with subsequent tumours incidence. In 9233 cases with breast cancer occurred in women resident in Turin, Italy, between 1985 and 1998 we observed a significant increased risk of 1.91 for subsequent cancer of corpus uteri, estimated with the age-standardised Aalen-Johansen incidence ratio (AJ-IRstand), and a significant increased risk of 1.29 for cancer possibly related to the radiotherapy of breast cancer. The peak of occurrence of those cancers was observed after 8 years of follow-up. Conclusion The increased risk of a cancer of the corpus uteri, also observed in other studies, is usually interpreted as the common shared risk factors such as low parity, early menarche and late onset of menopause. We also grouped together those cancers possibly associated to a previous local radiotherapy: the cumulative risk at 14 years is still not significant, however the AJ estimators showed a significant risk peak between the eighth and the ninth year. Finally, the proposed approach has been shown to be reliable and informative under several aspects. It allowed for a correct estimation of the risk, and for investigating
Valero, Antonio; Pasquali, Frédérique; De Cesare, Alessandra; Manfreda, Gerardo
2014-08-01
Current sampling plans assume a random distribution of microorganisms in food. However, food-borne pathogens are estimated to be heterogeneously distributed in powdered foods. This spatial distribution together with very low level of contaminations raises concern of the efficiency of current sampling plans for the detection of food-borne pathogens like Cronobacter and Salmonella in powdered foods such as powdered infant formula or powdered eggs. An alternative approach based on a Poisson distribution of the contaminated part of the lot (Habraken approach) was used in order to evaluate the probability of falsely accepting a contaminated lot of powdered food when different sampling strategies were simulated considering variables such as lot size, sample size, microbial concentration in the contaminated part of the lot and proportion of contaminated lot. The simulated results suggest that a sample size of 100g or more corresponds to the lower number of samples to be tested in comparison with sample sizes of 10 or 1g. Moreover, the number of samples to be tested greatly decrease if the microbial concentration is 1CFU/g instead of 0.1CFU/g or if the proportion of contamination is 0.05 instead of 0.01. Mean contaminations higher than 1CFU/g or proportions higher than 0.05 did not impact on the number of samples. The Habraken approach represents a useful tool for risk management in order to design a fit-for-purpose sampling plan for the detection of low levels of food-borne pathogens in heterogeneously contaminated powdered food. However, it must be outlined that although effective in detecting pathogens, these sampling plans are difficult to be applied since the huge number of samples that needs to be tested. Sampling does not seem an effective measure to control pathogens in powdered food.
Accurate Estimation of the Entropy of Rotation-Translation Probability Distributions.
Fogolari, Federico; Dongmo Foumthuim, Cedrix Jurgal; Fortuna, Sara; Soler, Miguel Angel; Corazza, Alessandra; Esposito, Gennaro
2016-01-12
The estimation of rotational and translational entropies in the context of ligand binding has been the subject of long-time investigations. The high dimensionality (six) of the problem and the limited amount of sampling often prevent the required resolution to provide accurate estimates by the histogram method. Recently, the nearest-neighbor distance method has been applied to the problem, but the solutions provided either address rotation and translation separately, therefore lacking correlations, or use a heuristic approach. Here we address rotational-translational entropy estimation in the context of nearest-neighbor-based entropy estimation, solve the problem numerically, and provide an exact and an approximate method to estimate the full rotational-translational entropy.
Schiebener, Johannes; Zamarian, Laura; Delazer, Margarete; Brand, Matthias
2011-11-01
In two experiments with healthy subjects, we used the Game of Dice Task (GDT), the Probability-Associated Gambling (PAG) task, the Iowa Gambling Task (IGT), and executive-function and logical thinking tasks to shed light on the underlying processes of decision making under risk. Results indicate that handling probabilities, as in the PAG task, is an important ingredient of GDT performance. Executive functions and logical thinking also play major roles in deciding in the GDT. Implicit feedback learning, as measured by the IGT, has little impact. Results suggest that good probability handling may compensate for the effects of weak executive functions in decisions under risk.
NASA Technical Reports Server (NTRS)
Pierson, Willard J., Jr.
1989-01-01
The values of the Normalized Radar Backscattering Cross Section (NRCS), sigma (o), obtained by a scatterometer are random variables whose variance is a known function of the expected value. The probability density function can be obtained from the normal distribution. Models for the expected value obtain it as a function of the properties of the waves on the ocean and the winds that generated the waves. Point estimates of the expected value were found from various statistics given the parameters that define the probability density function for each value. Random intervals were derived with a preassigned probability of containing that value. A statistical test to determine whether or not successive values of sigma (o) are truly independent was derived. The maximum likelihood estimates for wind speed and direction were found, given a model for backscatter as a function of the properties of the waves on the ocean. These estimates are biased as a result of the terms in the equation that involve natural logarithms, and calculations of the point estimates of the maximum likelihood values are used to show that the contributions of the logarithmic terms are negligible and that the terms can be omitted.
O'Donnell, Matthew J.; Horton, Gregg E.; Letcher, Benjamin H.
2010-01-01
Portable passive integrated transponder (PIT) tag antenna systems can be valuable in providing reliable estimates of the abundance of tagged Atlantic salmon Salmo salar in small streams under a wide range of conditions. We developed and employed PIT tag antenna wand techniques in two controlled experiments and an additional case study to examine the factors that influenced our ability to estimate population size. We used Pollock's robust-design capture–mark–recapture model to obtain estimates of the probability of first detection (p), the probability of redetection (c), and abundance (N) in the two controlled experiments. First, we conducted an experiment in which tags were hidden in fixed locations. Although p and c varied among the three observers and among the three passes that each observer conducted, the estimates of N were identical to the true values and did not vary among observers. In the second experiment using free-swimming tagged fish, p and c varied among passes and time of day. Additionally, estimates of N varied between day and night and among age-classes but were within 10% of the true population size. In the case study, we used the Cormack–Jolly–Seber model to examine the variation in p, and we compared counts of tagged fish found with the antenna wand with counts collected via electrofishing. In that study, we found that although p varied for age-classes, sample dates, and time of day, antenna and electrofishing estimates of N were similar, indicating that population size can be reliably estimated via PIT tag antenna wands. However, factors such as the observer, time of day, age of fish, and stream discharge can influence the initial and subsequent detection probabilities.
A novel approach to estimate the eruptive potential and probability in open conduit volcanoes.
De Gregorio, Sofia; Camarda, Marco
2016-07-26
In open conduit volcanoes, volatile-rich magma continuously enters into the feeding system nevertheless the eruptive activity occurs intermittently. From a practical perspective, the continuous steady input of magma in the feeding system is not able to produce eruptive events alone, but rather surplus of magma inputs are required to trigger the eruptive activity. The greater the amount of surplus of magma within the feeding system, the higher is the eruptive probability.Despite this observation, eruptive potential evaluations are commonly based on the regular magma supply, and in eruptive probability evaluations, generally any magma input has the same weight. Conversely, herein we present a novel approach based on the quantification of surplus of magma progressively intruded in the feeding system. To quantify the surplus of magma, we suggest to process temporal series of measurable parameters linked to the magma supply. We successfully performed a practical application on Mt Etna using the soil CO2 flux recorded over ten years.
A novel approach to estimate the eruptive potential and probability in open conduit volcanoes
De Gregorio, Sofia; Camarda, Marco
2016-01-01
In open conduit volcanoes, volatile-rich magma continuously enters into the feeding system nevertheless the eruptive activity occurs intermittently. From a practical perspective, the continuous steady input of magma in the feeding system is not able to produce eruptive events alone, but rather surplus of magma inputs are required to trigger the eruptive activity. The greater the amount of surplus of magma within the feeding system, the higher is the eruptive probability.Despite this observation, eruptive potential evaluations are commonly based on the regular magma supply, and in eruptive probability evaluations, generally any magma input has the same weight. Conversely, herein we present a novel approach based on the quantification of surplus of magma progressively intruded in the feeding system. To quantify the surplus of magma, we suggest to process temporal series of measurable parameters linked to the magma supply. We successfully performed a practical application on Mt Etna using the soil CO2 flux recorded over ten years. PMID:27456812
Optimal Allocation for the Estimation of Attributable Risk,
control studies . Various optimal strategies are examined using alternative exposure-specific disease rates. Odd Ratio, Relative Risk and Attributable Risk....This paper derives an expression for the optimum sampling allocation under the minimum variance criterion of the estimated attributable risk for case
INCLUDING TRANSITION PROBABILITIES IN NEST SURVIVAL ESTIMATION: A MAYFIELD MARKOV CHAIN
This manuscript is primarily an exploration of the statistical properties of nest-survival estimates for terrestrial songbirds. The Mayfield formulation described herein should allow researchers to test for complicated effects of stressors on daily survival and overall success, i...
NASA Astrophysics Data System (ADS)
Tan, Elcin
A new physically-based methodology for probable maximum precipitation (PMP) estimation is developed over the American River Watershed (ARW) using the Weather Research and Forecast (WRF-ARW) model. A persistent moisture flux convergence pattern, called Pineapple Express, is analyzed for 42 historical extreme precipitation events, and it is found that Pineapple Express causes extreme precipitation over the basin of interest. An average correlation between moisture flux convergence and maximum precipitation is estimated as 0.71 for 42 events. The performance of the WRF model is verified for precipitation by means of calibration and independent validation of the model. The calibration procedure is performed only for the first ranked flood event 1997 case, whereas the WRF model is validated for 42 historical cases. Three nested model domains are set up with horizontal resolutions of 27 km, 9 km, and 3 km over the basin of interest. As a result of Chi-square goodness-of-fit tests, the hypothesis that "the WRF model can be used in the determination of PMP over the ARW for both areal average and point estimates" is accepted at the 5% level of significance. The sensitivities of model physics options on precipitation are determined using 28 microphysics, atmospheric boundary layer, and cumulus parameterization schemes combinations. It is concluded that the best triplet option is Thompson microphysics, Grell 3D ensemble cumulus, and YSU boundary layer (TGY), based on 42 historical cases, and this TGY triplet is used for all analyses of this research. Four techniques are proposed to evaluate physically possible maximum precipitation using the WRF: 1. Perturbations of atmospheric conditions; 2. Shift in atmospheric conditions; 3. Replacement of atmospheric conditions among historical events; and 4. Thermodynamically possible worst-case scenario creation. Moreover, climate change effect on precipitation is discussed by emphasizing temperature increase in order to determine the
Davies, Christopher E; Giles, Lynne C; Glonek, Gary Fv
2017-01-01
One purpose of a longitudinal study is to gain insight of how characteristics at earlier points in time can impact on subsequent outcomes. Typically, the outcome variable varies over time and the data for each individual can be used to form a discrete path of measurements, that is a trajectory. Group-based trajectory modelling methods seek to identify subgroups of individuals within a population with trajectories that are more similar to each other than to trajectories in distinct groups. An approach to modelling the influence of covariates measured at earlier time points in the group-based setting is to consider models wherein these covariates affect the group membership probabilities. Models in which prior covariates impact the trajectories directly are also possible but are not considered here. In the present study, we compared six different methods for estimating the effect of covariates on the group membership probabilities, which have different approaches to account for the uncertainty in the group membership assignment. We found that when investigating the effect of one or several covariates on a group-based trajectory model, the full likelihood approach minimized the bias in the estimate of the covariate effect. In this '1-step' approach, the estimation of the effect of covariates and the trajectory model are carried out simultaneously. Of the '3-step' approaches, where the effect of the covariates is assessed subsequent to the estimation of the group-based trajectory model, only Vermunt's improved 3 step resulted in bias estimates similar in size to the full likelihood approach. The remaining methods considered resulted in considerably higher bias in the covariate effect estimates and should not be used. In addition to the bias empirically demonstrated for the probability regression approach, we have shown analytically that it is biased in general.
Zhang Yumin; Lum, Kai-Yew; Wang Qingguo
2009-03-05
In this paper, a H-infinity fault detection and diagnosis (FDD) scheme for a class of discrete nonlinear system fault using output probability density estimation is presented. Unlike classical FDD problems, the measured output of the system is viewed as a stochastic process and its square root probability density function (PDF) is modeled with B-spline functions, which leads to a deterministic space-time dynamic model including nonlinearities, uncertainties. A weighting mean value is given as an integral function of the square root PDF along space direction, which leads a function only about time and can be used to construct residual signal. Thus, the classical nonlinear filter approach can be used to detect and diagnose the fault in system. A feasible detection criterion is obtained at first, and a new H-infinity adaptive fault diagnosis algorithm is further investigated to estimate the fault. Simulation example is given to demonstrate the effectiveness of the proposed approaches.
Anderson, Christian C; Bauer, Adam Q; Holland, Mark R; Pakula, Michal; Laugier, Pascal; Bretthorst, G Larry; Miller, James G
2010-11-01
Quantitative ultrasonic characterization of cancellous bone can be complicated by artifacts introduced by analyzing acquired data consisting of two propagating waves (a fast wave and a slow wave) as if only one wave were present. Recovering the ultrasonic properties of overlapping fast and slow waves could therefore lead to enhancement of bone quality assessment. The current study uses Bayesian probability theory to estimate phase velocity and normalized broadband ultrasonic attenuation (nBUA) parameters in a model of fast and slow wave propagation. Calculations are carried out using Markov chain Monte Carlo with simulated annealing to approximate the marginal posterior probability densities for parameters in the model. The technique is applied to simulated data, to data acquired on two phantoms capable of generating two waves in acquired signals, and to data acquired on a human femur condyle specimen. The models are in good agreement with both the simulated and experimental data, and the values of the estimated ultrasonic parameters fall within expected ranges.
Wang, Bei; Wang, Xingyu; Zhang, Tao; Nakamura, Masatoshi
2013-01-01
An automatic sleep level estimation method was developed for monitoring and regulation of day time nap sleep. The recorded nap data is separated into continuous 5-second segments. Features are extracted from EEGs, EOGs and EMG. A parameter of sleep level is defined which is estimated based on the conditional probability of sleep stages. An exponential smoothing method is applied for the estimated sleep level. There were totally 12 healthy subjects, with an averaged age of 22 yeas old, participated into the experimental work. Comparing with sleep stage determination, the presented sleep level estimation method showed better performance for nap sleep interpretation. Real time monitoring and regulation of nap is realizable based on the developed technique.
NASA Astrophysics Data System (ADS)
Sun, Pengfei; Qin, Jun
2017-02-01
In this paper, a two-stage dual tree complex wavelet packet transform (DTCWPT) based speech enhancement algorithm has been proposed, in which a speech presence probability (SPP) estimator and a generalized minimum mean squared error (MMSE) estimator are developed. To overcome the drawback of signal distortions caused by down sampling of WPT, a two-stage analytic decomposition concatenating undecimated WPT (UWPT) and decimated WPT is employed. An SPP estimator in the DTCWPT domain is derived based on a generalized Gamma distribution of speech, and Gaussian noise assumption. The validation results show that the proposed algorithm can obtain enhanced perceptual evaluation of speech quality (PESQ), and segmental signal-to-noise ratio (SegSNR) at low SNR nonstationary noise, compared with other four state-of-the-art speech enhancement algorithms, including optimally modified LSA (OM-LSA), soft masking using a posteriori SNR uncertainty (SMPO), a posteriori SPP based MMSE estimation (MMSE-SPP), and adaptive Bayesian wavelet thresholding (BWT).
Dorval, Alan D
2008-08-15
The maximal information that the spike train of any neuron can pass on to subsequent neurons can be quantified as the neuronal firing pattern entropy. Difficulties associated with estimating entropy from small datasets have proven an obstacle to the widespread reporting of firing pattern entropies and more generally, the use of information theory within the neuroscience community. In the most accessible class of entropy estimation techniques, spike trains are partitioned linearly in time and entropy is estimated from the probability distribution of firing patterns within a partition. Ample previous work has focused on various techniques to minimize the finite dataset bias and standard deviation of entropy estimates from under-sampled probability distributions on spike timing events partitioned linearly in time. In this manuscript we present evidence that all distribution-based techniques would benefit from inter-spike intervals being partitioned in logarithmic time. We show that with logarithmic partitioning, firing rate changes become independent of firing pattern entropy. We delineate the entire entropy estimation process with two example neuronal models, demonstrating the robust improvements in bias and standard deviation that the logarithmic time method yields over two widely used linearly partitioned time approaches.
Estimating successive cancer risks in Lynch Syndrome families using a progressive three-state model.
Choi, Yun-Hee; Briollais, Laurent; Green, Jane; Parfrey, Patrick; Kopciuk, Karen
2014-02-20
Lynch Syndrome (LS) families harbor mutated mismatch repair genes,which predispose them to specific types of cancer. Because individuals within LS families can experience multiple cancers over their lifetime, we developed a progressive three-state model to estimate the disease risk from a healthy (state 0) to a first cancer (state 1) and then to a second cancer (state 2). Ascertainment correction of the likelihood was made to adjust for complex sampling designs with carrier probabilities for family members with missing genotype information estimated using their family's observed genotype and phenotype information in a one-step expectation-maximization algorithm. A sandwich variance estimator was employed to overcome possible model misspecification. The main objective of this paper is to estimate the disease risk (penetrance) for age at a second cancer after someone has experienced a first cancer that is also associated with a mutated gene. Simulation study results indicate that our approach generally provides unbiased risk estimates and low root mean squared errors across different family study designs, proportions of missing genotypes, and risk heterogeneities. An application to 12 large LS families from Newfoundland demonstrates that the risk for a second cancer was substantial and that the age at a first colorectal cancer significantly impacted the age at any LS subsequent cancer. This study provides new insights for developing more effective management of mutation carriers in LS families by providing more accurate multiple cancer risk estimates.
Radiobiologic risk estimation from dental radiology. Part II. Cancer incidence and fatality
Underhill, T.E.; Kimura, K.; Chilvarquer, I.; McDavid, W.D.; Langlais, R.P.; Preece, J.W.; Barnwell, G.
1988-08-01
With the use of the measured absorbed doses from part I of this article, the specific radiobiologic risk to the patient from (1) five different panoramic machines with rare-earth screens, (2) a 20-film complete-mouth survey with E-speed film, long round cone, (3) a 20-film complete-mouth survey with E-speed film, long rectangular cone, (4) a 4-film interproximal survey with E-speed film, long round cone, and (5) a 4-film interproximal survey with E-speed film, long rectangular cone, was calculated. The estimated risks are expressed in two ways: the probability of radiation-induced cancer in specific organs per million examinations and the probability of expression of a fatal cancer per million examinations. The highest risks calculated were from the complete-mouth survey with the use of round collimation. The lowest risks calculated were from panoramic radiography and four interproximal radiographs with rectangular collimation.
NASA Technical Reports Server (NTRS)
Huddleston, Lisa; Roeder, WIlliam P.; Merceret, Francis J.
2011-01-01
A new technique has been developed to estimate the probability that a nearby cloud-to-ground lightning stroke was within a specified radius of any point of interest. This process uses the bivariate Gaussian distribution of probability density provided by the current lightning location error ellipse for the most likely location of a lightning stroke and integrates it to determine the probability that the stroke is inside any specified radius of any location, even if that location is not centered on or even within the location error ellipse. This technique is adapted from a method of calculating the probability of debris collision with spacecraft. Such a technique is important in spaceport processing activities because it allows engineers to quantify the risk of induced current damage to critical electronics due to nearby lightning strokes. This technique was tested extensively and is now in use by space launch organizations at Kennedy Space Center and Cape Canaveral Air Force station. Future applications could include forensic meteorology.
Non-parametric estimation of spatial variation in relative risk.
Kelsall, J E; Diggle, P J
We consider the problem of estimating the spatial variation in relative risks of two diseases, say, over a geographical region. Using an underlying Poisson point process model, we approach the problem as one of density ratio estimation implemented with a non-parametric kernel smoothing method. In order to assess the significance of any local peaks or troughs in the estimated risk surface, we introduce pointwise tolerance contours which can enhance a greyscale image plot of the estimate. We also propose a Monte Carlo test of the null hypothesis of constant risk over the whole region, to avoid possible over-interpretation of the estimated risk surface. We illustrate the capabilities of the methodology with two epidemiological examples.
Parametric Estimation in a Recurrent Competing Risks Model.
Taylor, Laura L; Peña, Edsel A
2013-01-01
A resource-efficient approach to making inferences about the distributional properties of the failure times in a competing risks setting is presented. Efficiency is gained by observing recurrences of the competing risks over a random monitoring period. The resulting model is called the recurrent competing risks model (RCRM) and is coupled with two repair strategies whenever the system fails. Maximum likelihood estimators of the parameters of the marginal distribution functions associated with each of the competing risks and also of the system lifetime distribution function are presented. Estimators are derived under perfect and partial repair strategies. Consistency and asymptotic properties of the estimators are obtained. The estimation methods are applied to a data set of failures for cars under warranty. Simulation studies are used to ascertain the small sample properties and the efficiency gains of the resulting estimators.
Development of a statistical tool for the estimation of riverbank erosion probability
NASA Astrophysics Data System (ADS)
Varouchakis, E. A.; Giannakis, G. V.; Lilli, M. A.; Ioannidou, E.; Nikolaidis, N. P.; Karatzas, G. P.
2015-06-01
Riverbank erosion affects river morphology and local habitat and results in riparian land loss, property and infrastructure damage, and ultimately flood defence weakening. An important issue concerning riverbank erosion is the identification of the vulnerable areas in order to predict river changes and assist stream management/restoration. An approach to predict vulnerable to erosion areas is to quantify the erosion probability by identifying the underlying relations between riverbank erosion and geomorphological or hydrological variables that prevent or stimulate erosion. In the present work, a combined deterministic and statistical methodology is proposed to predict the probability of presence or absence of erosion in a river section. A physically based model determines the vulnerable to erosion locations by quantifying the potential eroded area. The derived results are used to determine validation locations for the statistical tool performance evaluation. The statistical tool is based on a series of independent local variables and employs the Logistic Regression methodology. It is developed in two forms, Logistic Regression and Locally Weighted Logistic Regression, which both deliver useful and accurate results. The second form though provides the most accurate results as it validates the presence or absence of erosion at all validation locations. The proposed methodology is easy to use, accurate and can be applied to any region and river.
Development of a statistical tool for the estimation of riverbank erosion probability
NASA Astrophysics Data System (ADS)
Varouchakis, E. A.; Giannakis, G. V.; Lilli, M. A.; Ioannidou, E.; Nikolaidis, N. P.; Karatzas, G. P.
2016-01-01
Riverbank erosion affects river morphology and local habitat, and results in riparian land loss, property and infrastructure damage, and ultimately flood defence weakening. An important issue concerning riverbank erosion is the identification of the vulnerable areas in order to predict river changes and assist stream management/restoration. An approach to predict areas vulnerable to erosion is to quantify the erosion probability by identifying the underlying relations between riverbank erosion and geomorphological or hydrological variables that prevent or stimulate erosion. In the present work, a statistical methodology is proposed to predict the probability of the presence or absence of erosion in a river section. A physically based model determines the locations vulnerable to erosion by quantifying the potential eroded area. The derived results are used to determine validation locations for the evaluation of the statistical tool performance. The statistical tool is based on a series of independent local variables and employs the logistic regression methodology. It is developed in two forms, logistic regression and locally weighted logistic regression, which both deliver useful and accurate results. The second form, though, provides the most accurate results as it validates the presence or absence of erosion at all validation locations. The proposed tool is easy to use and accurate and can be applied to any region and river.
Categorizing sources of risk and the estimated magnitude of risk.
Aragonés, Juan Ignacio; Moyano, Emilio; Talayero, Fernando
2008-05-01
The social perception of risk is considered a multidimensional task, yet little attention has been paid to the cognitive components that organize sources of risk, despite their having been discovered in various research studies. This study attempts to concretely analyze the cultural dimension involved in those processes. In the first phase, we tried to discover to what extent sources of risk are organized into the same categories by people from different countries. In order to do so, two groups of participants were formed: 60 Spanish psychology students and 60 Chilean psychology students classified 43 sources of risk into different groups according to the criteria they found appropriate. The two samples classified risk into identical groups: acts of violence, drugs, electricity and home appliances, household chemicals, chemicals in the environment, public construction projects, transportation, sports, and natural disasters. In a second study, 100 Spanish and 84 Chilean students were asked to evaluate the magnitude of the damage incurred by 17 sources of risk. In both groups, it was observed that the evaluation of damage resulting from each source of risk was affected by its category.
A generic computerized method for estimate of familial risks.
Colombet, Isabelle; Xu, Yigang; Jaulent, Marie-Christine; Desages, Daniel; Degoulet, Patrice; Chatellier, Gilles
2002-01-01
Most guidelines developed for cancers screening and for cardiovascular risk management use rules to estimate familial risk. These rules are complex, difficult to memorize, and need to collect a complete pedigree. This paper describes a generic computerized method to estimate familial risks and its implementation in an internet-based application. The program is based on 3 generic models: a model of the family; a model of familial risk; a display model for the pedigree. The model of family allows to represent each member of the family and to construct and display a family tree. The model of familial risk is generic and allows easy update of the program with new diseases or new rules. It was possible to implement guidelines dealing with breast and colorectal cancer and cardiovascular diseases prevention. First evaluation with general practitioners showed that the program was usable. Impact on quality of familial risk estimate should be more documented. PMID:12463810
Wu, Shih-Wei; Delgado, Mauricio R; Maloney, Laurence T
2011-06-15
In decision under risk, people choose between lotteries that contain a list of potential outcomes paired with their probabilities of occurrence. We previously developed a method for translating such lotteries to mathematically equivalent "motor lotteries." The probability of each outcome in a motor lottery is determined by the subject's noise in executing a movement. In this study, we used functional magnetic resonance imaging in humans to compare the neural correlates of monetary outcome and probability in classical lottery tasks in which information about probability was explicitly communicated to the subjects and in mathematically equivalent motor lottery tasks in which probability was implicit in the subjects' own motor noise. We found that activity in the medial prefrontal cortex (mPFC) and the posterior cingulate cortex quantitatively represent the subjective utility of monetary outcome in both tasks. For probability, we found that the mPFC significantly tracked the distortion of such information in both tasks. Specifically, activity in mPFC represents probability information but not the physical properties of the stimuli correlated with this information. Together, the results demonstrate that mPFC represents probability from two distinct forms of decision under risk.
Precise, unbiased estimates of population size are an essential tool for fisheries management. For a wide variety of salmonid fishes, redd counts from a sample of reaches are commonly used to monitor annual trends in abundance. Using a 9-year time series of georeferenced censuses...
Glaser, Craig; Trommershäuser, Julia; Mamassian, Pascal; Maloney, Laurence T
2012-04-01
Decision makers typically overweight small probabilities and underweight large probabilities. However, there are recent reports that when probability is presented in the form of relative frequencies, this typical pattern reverses. We tested this hypothesis by comparing decision making in two tasks: In one task, probability was stated numerically, and in the other task, it was conveyed through a visual representation. In the visual task, participants chose whether a "stochastic bullet" should be fired at either a large target for a small reward or a small target for a large reward. Participants' knowledge of probability in the visual task was the result of extensive practice firing bullets at targets. In the classical numerical task, participants chose between pairs of lotteries with probabilities and rewards matched to the probabilities and rewards in the visual task. We found that participants' probability-weighting functions were significantly different in the two tasks, but the pattern for the visual task was the typical, not the reversed, pattern.
Wullenweber, Andrea; Kroner, Oliver; Kohrman, Melissa; Maier, Andrew; Dourson, Michael; Rak, Andrew; Wexler, Philip; Tomljanovic, Chuck
2008-11-15
The rate of chemical synthesis and use has outpaced the development of risk values and the resolution of risk assessment methodology questions. In addition, available risk values derived by different organizations may vary due to scientific judgments, mission of the organization, or use of more recently published data. Further, each organization derives values for a unique chemical list so it can be challenging to locate data on a given chemical. Two Internet resources are available to address these issues. First, the International Toxicity Estimates for Risk (ITER) database (www.tera.org/iter) provides chronic human health risk assessment data from a variety of organizations worldwide in a side-by-side format, explains differences in risk values derived by different organizations, and links directly to each organization's website for more detailed information. It is also the only database that includes risk information from independent parties whose risk values have undergone independent peer review. Second, the Risk Information Exchange (RiskIE) is a database of in progress chemical risk assessment work, and includes non-chemical information related to human health risk assessment, such as training modules, white papers and risk documents. RiskIE is available at http://www.allianceforrisk.org/RiskIE.htm, and will join ITER on National Library of Medicine's TOXNET (http://toxnet.nlm.nih.gov/). Together, ITER and RiskIE provide risk assessors essential tools for easily identifying and comparing available risk data, for sharing in progress assessments, and for enhancing interaction among risk assessment groups to decrease duplication of effort and to harmonize risk assessment procedures across organizations.
Miles McQueen; Wayne Boyer; Mark Flynn; Sam Alessi
2006-03-01
For the past year we have applied a variety of risk assessment technologies to evaluate the risk to critical infrastructure from cyber attacks on control systems. More recently, we identified the need for a stand alone control system risk reduction estimation tool to provide owners and operators of control systems with a more useable, reliable, and credible method for managing the risks from cyber attack. Risk is defined as the probability of a successful attack times the value of the resulting loss, typically measured in lives and dollars. Qualitative and ad hoc techniques for measuring risk do not provide sufficient support for cost benefit analyses associated with cyber security mitigation actions. To address the need for better quantitative risk reduction models we surveyed previous quantitative risk assessment research; evaluated currently available tools; developed new quantitative techniques [17] [18]; implemented a prototype analysis tool to demonstrate how such a tool might be used; used the prototype to test a variety of underlying risk calculational engines (e.g. attack tree, attack graph); and identified technical and research needs. We concluded that significant gaps still exist and difficult research problems remain for quantitatively assessing the risk to control system components and networks, but that a useable quantitative risk reduction estimation tool is not beyond reach.
Park, Dong-Uk; Colt, Joanne S.; Baris, Dalsu; Schwenn, Molly; Karagas, Margaret R.; Armenti, Karla R.; Johnson, Alison; Silverman, Debra T; Stewart, Patricia A
2014-01-01
We describe here an approach for estimating the probability that study subjects were exposed to metalworking fluids (MWFs) in a population-based case-control study of bladder cancer. Study subject reports on the frequency of machining and use of specific MWFs (straight, soluble, and synthetic/semi-synthetic) were used to estimate exposure probability when available. Those reports also were used to develop estimates for job groups, which were then applied to jobs without MWF reports. Estimates using both cases and controls and controls only were developed. The prevalence of machining varied substantially across job groups (10-90%), with the greatest percentage of jobs that machined being reported by machinists and tool and die workers. Reports of straight and soluble MWF use were fairly consistent across job groups (generally, 50-70%). Synthetic MWF use was lower (13-45%). There was little difference in reports by cases and controls vs. controls only. Approximately, 1% of the entire study population was assessed as definitely exposed to straight or soluble fluids in contrast to 0.2% definitely exposed to synthetic/semi-synthetics. A comparison between the reported use of the MWFs and the US production levels by decade found high correlations (r generally >0.7). Overall, the method described here is likely to have provided a systematic and reliable ranking that better reflects the variability of exposure to three types of MWFs than approaches applied in the past. PMID:25256317
Estimates of coextinction risk: how anuran parasites respond to the extinction of their hosts.
Campião, Karla Magalhães; de Aquino Ribas, Augusto Cesar; Cornell, Stephen J; Begon, Michael; Tavares, Luiz Eduardo Roland
2015-12-01
Amphibians are known as the most threatened vertebrate group. One of the outcomes of a species' extinction is the coextinction of its dependents. Here, we estimate the extinction risk of helminth parasites of South America anurans. Parasite coextinction probabilities were modeled, assuming parasite specificity and host vulnerability to extinction as determinants. Parasite species associated with few hosts were the most prone to extinction, and extinction risk varied amongst helminth species of different taxonomic groups and life cycle complexity. Considering host vulnerability in the model decreased the extinction probability of most parasites species. However, parasite specificity and host vulnerability combined to increase the extinction probabilities of 44% of the helminth species reported in a single anuran species.
Soil-ecological risks for soil degradation estimation
NASA Astrophysics Data System (ADS)
Trifonova, Tatiana; Shirkin, Leonid; Kust, German; Andreeva, Olga
2016-04-01
Soil degradation includes the processes of soil properties and quality worsening, primarily from the point of view of their productivity and decrease of ecosystem services quality. Complete soil cover destruction and/or functioning termination of soil forms of organic life are considered as extreme stages of soil degradation, and for the fragile ecosystems they are normally considered in the network of their desertification, land degradation and droughts /DLDD/ concept. Block-model of ecotoxic effects, generating soil and ecosystem degradation, has been developed as a result of the long-term field and laboratory research of sod-podzol soils, contaminated with waste, containing heavy metals. The model highlights soil degradation mechanisms, caused by direct and indirect impact of ecotoxicants on "phytocenosis- soil" system and their combination, frequently causing synergistic effect. The sequence of occurring changes here can be formalized as a theory of change (succession of interrelated events). Several stages are distinguished here - from heavy metals leaching (releasing) in waste and their migration downward the soil profile to phytoproductivity decrease and certain phytocenosis composition changes. Phytoproductivity decrease leads to the reduction of cellulose content introduced into the soil. The described feedback mechanism acts as a factor of sod-podzolic soil self-purification and stability. It has been shown, that using phytomass productivity index, integrally reflecting the worsening of soil properties complex, it is possible to solve the problems dealing with the dose-reflecting reactions creation and determination of critical levels of load for phytocenosis and corresponding soil-ecological risks. Soil-ecological risk in "phytocenosis- soil" system means probable negative changes and the loss of some ecosystem functions during the transformation process of dead organic substance energy for the new biomass composition. Soil-ecological risks estimation is
Fonnesbeck, Christopher J; McPheeters, Melissa L; Krishnaswami, Shanthi; Lindegren, Mary Louise; Reimschisel, Tyler
2013-09-01
Though the control of blood phenylalanine (Phe) levels is essential for minimizing impairment in individuals with phenylketonuria (PKU), the empirical basis for the selection of specific blood Phe levels as targets has not been evaluated. We evaluated the current evidence that particular Phe levels are optimal for minimizing or avoiding cognitive impairment in individuals with PKU. This work uses meta-estimates of blood Phe-IQ correlation to predict the probability of low IQ for a range of Phe levels. We believe this metric is easily interpretable by clinicians, and hence useful in making recommendations for Phe intake. The median baseline association of Phe with IQ was estimated to be negative, both in the context of historical (median = -0.026, 95 % BCI = [-0.040, -0.013]) and concurrent (-0.007, [-0.014, 0.000]) measurement of Phe relative to IQ. The estimated additive fixed effect of critical period Phe measurement was also nominally negative for historical measurement (-0.010, [-0.022, 0.003]) and positive for concurrent measurement (0.007, [-0.018, 0.035]). Probabilities corresponding to historical measures of blood Phe demonstrated an increasing chance of low IQ with increasing Phe, with a stronger association seen between blood Phe measured during the critical period than later. In contrast, concurrently-measured Phe was more weakly correlated with the probability of low IQ, though the correlation is still positive, irrespective of whether Phe was measured during the critical or non-critical period. This meta-analysis illustrates the utility of a Bayesian hierarchical approach for not only combining information from a set of candidate studies, but also for combining different types of data to estimate parameters of interest.
NASA Astrophysics Data System (ADS)
Katsura, K.; Ogata, Y.
2004-12-01
Reasenberg and Jones [Science, 1989, 1994] proposed the aftershock probability forecasting based on the joint distribution [Utsu, J. Fac. Sci. Hokkaido Univ., 1970] of the modified Omori formula of aftershock decay and Gutenberg-Richter law of magnitude frequency, where the respective parameters are estimated by the maximum likelihood method [Ogata, J. Phys. Earth, 1983; Utsu, Geophys Bull. Hokkaido Univ., 1965, Aki, Bull. Earthq. Res. Inst., 1965]. The public forecast has been implemented by the responsible agencies in California and Japan. However, a considerable difficulty in the above procedure is that, due to the contamination of arriving seismic waves, detection rate of aftershocks is extremely low during a period immediately after the main shock, say, during the first day, when the forecasting is most critical for public in the affected area. Therefore, for the forecasting of a probability during such a period, they adopt a generic model with a set of the standard parameter values in California or Japan. For an effective and realistic estimation, I propose to utilize the statistical model introduced by Ogata and Katsura [Geophys. J. Int., 1993] for the simultaneous estimation of the b-values of Gutenberg-Richter law together with detection-rate (probability) of earthquakes of each magnitude-band from the provided data of all detected events, where the both parameters are allowed for changing in time. Thus, by using all detected aftershocks from the beginning of the period, we can estimate the underlying modified Omori rate of both detected and undetected events and their b-value changes, taking the time-varying missing rates of events into account. The similar computation is applied to the ETAS model for complex aftershock activity or regional seismicity where substantial missing events are expected immediately after a large aftershock or another strong earthquake in the vicinity. Demonstrations of the present procedure will be shown for the recent examples
Haapea, Marianne; Veijola, Juha; Tanskanen, Päivikki; Jääskeläinen, Erika; Isohanni, Matti; Miettunen, Jouko
2011-12-30
Low participation is a potential source of bias in population-based studies. This article presents use of inverse probability weighting (IPW) in adjusting for non-participation in estimation of brain volumes among subjects with schizophrenia. Altogether 101 schizophrenia subjects and 187 non-psychotic comparison subjects belonging to the Northern Finland 1966 Birth Cohort were invited to participate in a field study during 1999-2001. Volumes of grey matter (GM), white matter (WM) and cerebrospinal fluid (CSF) were compared between the 54 participating schizophrenia subjects and 100 comparison subjects. IPW by illness-related auxiliary variables did not affect the estimated GM and WM mean volumes, but increased the estimated CSF mean volume in schizophrenia subjects. When adjusted for intracranial volume and family history of psychosis, IPW led to smaller estimated GM and WM mean volumes. Especially IPW by a disability pension and a higher amount of hospitalisation due to psychosis had effect on estimated mean brain volumes. The IPW method can be used to improve estimates affected by non-participation by reflecting the true differences in the target population.
Uncertainties in Estimates of the Risks of Late Effects from Space Radiation
NASA Technical Reports Server (NTRS)
Cucinotta, F. A.; Schimmerling, W.; Wilson, J. W.; Peterson, L. E.; Saganti, P.; Dicelli, J. F.
2002-01-01
The health risks faced by astronauts from space radiation include cancer, cataracts, hereditary effects, and non-cancer morbidity and mortality risks related to the diseases of the old age. Methods used to project risks in low-Earth orbit are of questionable merit for exploration missions because of the limited radiobiology data and knowledge of galactic cosmic ray (GCR) heavy ions, which causes estimates of the risk of late effects to be highly uncertain. Risk projections involve a product of many biological and physical factors, each of which has a differential range of uncertainty due to lack of data and knowledge. Within the linear-additivity model, we use Monte-Carlo sampling from subjective uncertainty distributions in each factor to obtain a Maximum Likelihood estimate of the overall uncertainty in risk projections. The resulting methodology is applied to several human space exploration mission scenarios including ISS, lunar station, deep space outpost, and Mar's missions of duration of 360, 660, and 1000 days. The major results are the quantification of the uncertainties in current risk estimates, the identification of factors that dominate risk projection uncertainties, and the development of a method to quantify candidate approaches to reduce uncertainties or mitigate risks. The large uncertainties in GCR risk projections lead to probability distributions of risk that mask any potential risk reduction using the "optimization" of shielding materials or configurations. In contrast, the design of shielding optimization approaches for solar particle events and trapped protons can be made at this time, and promising technologies can be shown to have merit using our approach. The methods used also make it possible to express risk management objectives in terms of quantitative objective's, i.e., the number of days in space without exceeding a given risk level within well defined confidence limits.
Vsevolozhskaya, Olga A; Anthony, James C
2016-06-29
Measured as elapsed time from first use to dependence syndrome onset, the estimated "induction interval" for cocaine is thought to be short relative to the cannabis interval, but little is known about risk of becoming dependent during first months after onset of use. Virtually all published estimates for this facet of drug dependence epidemiology are from life histories elicited years after first use. To improve estimation, we turn to new month-wise data from nationally representative samples of newly incident drug users identified via probability sampling and confidential computer-assisted self-interviews for the United States National Surveys on Drug Use and Health, 2004-2013. Standardized modules assessed first and most recent use, and dependence syndromes, for each drug subtype. A four-parameter Hill function depicts the drug dependence transition for subgroups defined by units of elapsed time from first to most recent use, with an expectation of greater cocaine dependence transitions for cocaine versus cannabis. This study's novel estimates for cocaine users one month after first use show 2-4% with cocaine dependence; 12-17% are dependent when use has persisted. Corresponding cannabis estimates are 0-1% after one month, but 10-23% when use persists. Duration or persistence of cannabis smoking beyond an initial interval of a few months of use seems to be a signal of noteworthy risk for, or co-occurrence of, rapid-onset cannabis dependence, not too distant from cocaine estimates, when we sort newly incident users into subgroups defined by elapsed time from first to most recent use. Copyright © 2016 John Wiley & Sons, Ltd.
Berrino, Jacopo; Berrino, Franco; Francisci, Silvia; Peissel, Bernard; Azzollini, Jacopo; Pensotti, Valeria; Radice, Paolo; Pasanisi, Patrizia; Manoukian, Siranoush
2015-03-01
We have designed the user-friendly COS software with the intent to improve estimation of the probability of a family carrying a deleterious BRCA gene mutation. The COS software is similar to the widely-used Bayesian-based BRCAPRO software, but it incorporates improved assumptions on cancer incidence in women with and without a deleterious mutation, takes into account relatives up to the fourth degree and allows researchers to consider an hypothetical third gene or a polygenic model of inheritance. Since breast cancer incidence and penetrance increase over generations, we estimated birth-cohort-specific incidence and penetrance curves. We estimated breast and ovarian cancer penetrance in 384 BRCA1 and 229 BRCA2 mutated families. We tested the COS performance in 436 Italian breast/ovarian cancer families including 79 with BRCA1 and 27 with BRCA2 mutations. The area under receiver operator curve (AUROC) was 84.4 %. The best probability threshold for offering the test was 22.9 %, with sensitivity 80.2 % and specificity 80.3 %. Notwithstanding very different assumptions, COS results were similar to BRCAPRO v6.0.
Ferrante, L; Bompadre, S; Leone, L; Montanari, M P
2005-06-01
Time-kill curves have frequently been employed to study the antimicrobial effects of antibiotics. The relevance of pharmacodynamic modeling to these investigations has been emphasized in many studies of bactericidal kinetics. Stochastic models are needed that take into account the randomness of the mechanisms of both bacterial growth and bacteria-drug interactions. However, most of the models currently used to describe antibiotic activity against microorganisms are deterministic. In this paper we examine a stochastic differential equation representing a stochastic version of a pharmacodynamic model of bacterial growth undergoing random fluctuations, and derive its solution, mean value and covariance structure. An explicit likelihood function is obtained both when the process is observed continuously over a period of time and when data is sampled at time points, as is the custom in these experimental conditions. Some asymptotic properties of the maximum likelihood estimators for the model parameters are discussed. The model is applied to analyze in vitro time-kill data and to estimate model parameters; the probability of the bacterial population size dropping below some critical threshold is also evaluated. Finally, the relationship between bacterial extinction probability and the pharmacodynamic parameters estimated is discussed.
Juslin, Peter; Lindskog, Marcus; Mayerhofer, Bastian
2015-03-01
While a wealth of evidence suggests that humans tend to rely on additive cue combination to make controlled judgments, many of the normative rules for probability combination require multiplicative combination. In this article, the authors combine the experimental paradigms on probability reasoning and multiple-cue judgment to allow a comparison between formally identical tasks that involve probability vs. other task contents. The purpose was to investigate if people have cognitive algorithms for the combination, specifically, of probability, affording multiplicative combination in the context of probability. Three experiments suggest that, although people show some signs of a qualitative understanding of the combination rules that are specific to probability, in all but the simplest cases they lack the cognitive algorithms needed for multiplication, but instead use a variety of additive heuristics to approximate the normative combination. Although these heuristics are surprisingly accurate, normative combination is not consistently achieved until the problems are framed in an additive way.
Lu, Dan; Zhang, Guannan; Webster, Clayton G.; ...
2016-12-30
In this paper, we develop an improved multilevel Monte Carlo (MLMC) method for estimating cumulative distribution functions (CDFs) of a quantity of interest, coming from numerical approximation of large-scale stochastic subsurface simulations. Compared with Monte Carlo (MC) methods, that require a significantly large number of high-fidelity model executions to achieve a prescribed accuracy when computing statistical expectations, MLMC methods were originally proposed to significantly reduce the computational cost with the use of multifidelity approximations. The improved performance of the MLMC methods depends strongly on the decay of the variance of the integrand as the level increases. However, the main challengemore » in estimating CDFs is that the integrand is a discontinuous indicator function whose variance decays slowly. To address this difficult task, we approximate the integrand using a smoothing function that accelerates the decay of the variance. In addition, we design a novel a posteriori optimization strategy to calibrate the smoothing function, so as to balance the computational gain and the approximation error. The combined proposed techniques are integrated into a very general and practical algorithm that can be applied to a wide range of subsurface problems for high-dimensional uncertainty quantification, such as a fine-grid oil reservoir model considered in this effort. The numerical results reveal that with the use of the calibrated smoothing function, the improved MLMC technique significantly reduces the computational complexity compared to the standard MC approach. Finally, we discuss several factors that affect the performance of the MLMC method and provide guidance for effective and efficient usage in practice.« less
Lu, Dan; Zhang, Guannan; Webster, Clayton G.; Barbier, Charlotte N.
2016-12-30
In this paper, we develop an improved multilevel Monte Carlo (MLMC) method for estimating cumulative distribution functions (CDFs) of a quantity of interest, coming from numerical approximation of large-scale stochastic subsurface simulations. Compared with Monte Carlo (MC) methods, that require a significantly large number of high-fidelity model executions to achieve a prescribed accuracy when computing statistical expectations, MLMC methods were originally proposed to significantly reduce the computational cost with the use of multifidelity approximations. The improved performance of the MLMC methods depends strongly on the decay of the variance of the integrand as the level increases. However, the main challenge in estimating CDFs is that the integrand is a discontinuous indicator function whose variance decays slowly. To address this difficult task, we approximate the integrand using a smoothing function that accelerates the decay of the variance. In addition, we design a novel a posteriori optimization strategy to calibrate the smoothing function, so as to balance the computational gain and the approximation error. The combined proposed techniques are integrated into a very general and practical algorithm that can be applied to a wide range of subsurface problems for high-dimensional uncertainty quantification, such as a fine-grid oil reservoir model considered in this effort. The numerical results reveal that with the use of the calibrated smoothing function, the improved MLMC technique significantly reduces the computational complexity compared to the standard MC approach. Finally, we discuss several factors that affect the performance of the MLMC method and provide guidance for effective and efficient usage in practice.
Sensitivity of health risk estimates to air quality adjustment procedure
Whitfield, R.G.
1997-06-30
This letter is a summary of risk results associated with exposure estimates using two-parameter Weibull and quadratic air quality adjustment procedures (AQAPs). New exposure estimates were developed for children and child-occurrences, six urban areas, and five alternative air quality scenarios. In all cases, the Weibull and quadratic results are compared to previous results, which are based on a proportional AQAP.
Amundson, Courtney L.; Royle, J. Andrew; Handel, Colleen M.
2014-01-01
Imperfect detection during animal surveys biases estimates of abundance and can lead to improper conclusions regarding distribution and population trends. Farnsworth et al. (2005) developed a combined distance-sampling and time-removal model for point-transect surveys that addresses both availability (the probability that an animal is available for detection; e.g., that a bird sings) and perceptibility (the probability that an observer detects an animal, given that it is available for detection). We developed a hierarchical extension of the combined model that provides an integrated analysis framework for a collection of survey points at which both distance from the observer and time of initial detection are recorded. Implemented in a Bayesian framework, this extension facilitates evaluating covariates on abundance and detection probability, incorporating excess zero counts (i.e. zero-inflation), accounting for spatial autocorrelation, and estimating population density. Species-specific characteristics, such as behavioral displays and territorial dispersion, may lead to different patterns of availability and perceptibility, which may, in turn, influence the performance of such hierarchical models. Therefore, we first test our proposed model using simulated data under different scenarios of availability and perceptibility. We then illustrate its performance with empirical point-transect data for a songbird that consistently produces loud, frequent, primarily auditory signals, the Golden-crowned Sparrow (Zonotrichia atricapilla); and for 2 ptarmigan species (Lagopus spp.) that produce more intermittent, subtle, and primarily visual cues. Data were collected by multiple observers along point transects across a broad landscape in southwest Alaska, so we evaluated point-level covariates on perceptibility (observer and habitat), availability (date within season and time of day), and abundance (habitat, elevation, and slope), and included a nested point
2011-01-01
Background Automated adverse outcome surveillance tools and methods have potential utility in quality improvement and medical product surveillance activities. Their use for assessing hospital performance on the basis of patient outcomes has received little attention. We compared risk-adjusted sequential probability ratio testing (RA-SPRT) implemented in an automated tool to Massachusetts public reports of 30-day mortality after isolated coronary artery bypass graft surgery. Methods A total of 23,020 isolated adult coronary artery bypass surgery admissions performed in Massachusetts hospitals between January 1, 2002 and September 30, 2007 were retrospectively re-evaluated. The RA-SPRT method was implemented within an automated surveillance tool to identify hospital outliers in yearly increments. We used an overall type I error rate of 0.05, an overall type II error rate of 0.10, and a threshold that signaled if the odds of dying 30-days after surgery was at least twice than expected. Annual hospital outlier status, based on the state-reported classification, was considered the gold standard. An event was defined as at least one occurrence of a higher-than-expected hospital mortality rate during a given year. Results We examined a total of 83 hospital-year observations. The RA-SPRT method alerted 6 events among three hospitals for 30-day mortality compared with 5 events among two hospitals using the state public reports, yielding a sensitivity of 100% (5/5) and specificity of 98.8% (79/80). Conclusions The automated RA-SPRT method performed well, detecting all of the true institutional outliers with a small false positive alerting rate. Such a system could provide confidential automated notification to local institutions in advance of public reporting providing opportunities for earlier quality improvement interventions. PMID:22168892
Probabilistic methodology for estimating radiation-induced cancer risk
Dunning, D.E. Jr.; Leggett, R.W.; Williams, L.R.
1981-01-01
The RICRAC computer code was developed at Oak Ridge National Laboratory to provide a versatile and convenient methodology for radiation risk assessment. The code allows as input essentially any dose pattern commonly encountered in risk assessments for either acute or chronic exposures, and it includes consideration of the age structure of the exposed population. Results produced by the analysis include the probability of one or more radiation-induced cancer deaths in a specified population, expected numbers of deaths, and expected years of life lost as a result of premature fatalities. These calculatons include consideration of competing risks of death from all other causes. The program also generates a probability frequency distribution of the expected number of cancers in any specified cohort resulting from a given radiation dose. The methods may be applied to any specified population and dose scenario.
Kim, Yoo Mee; Hyun, Noo-Rie; Shon, Ho-Sang; Kim, Hae-Soon; Park, So-Young; Park, Il-Hyung; Chung, Yoon-Sok; Jung, Hong-Geun; Kim, Do-Hee; Lim, Sung-Kil
2008-12-01
This cross-sectional, observational study was designed to identify clinical risk factors of osteoporosis and fractures in Korean women to validate the probability of osteoporosis and subsequent fractures. A total of 1541 Korean women were recruited nationally. Fracture history of any site, risk factors of osteoporosis, and fall-related risk factors were surveyed and physical performance tests were conducted. Peripheral dual-energy X-ray absorptiometry was used to measure calcaneus bone mineral density (BMD). The number of positive responses on the modified 1-min osteoporosis risk test was related to the risk of osteoporosis. The frequency of osteoporosis was higher in those with a height reduction of >4 cm and a reduced body mass index (BMI). Multivariate analysis showed that older age and lower BMI were related to higher relative risk of osteoporosis. Time required to stand up from a chair and questions related to fall injury were significantly related to clinical fracture history of any site. Multivariate analysis showed that the relative risk of fractures at any site was higher in older subjects with a lower T-score and parental hip fracture history. This study shows that age and BMI are the most significant clinical risk factors for osteoporosis and that age, BMD, and parental history of hip fracture are highly applicable risk factors for validating the probability of osteoporotic fractures in Korean women.
Uncertainties in estimates of the risks of late effects from space radiation
NASA Technical Reports Server (NTRS)
Cucinotta, F. A.; Schimmerling, W.; Wilson, J. W.; Peterson, L. E.; Saganti, P. B.; Dicello, J. F.
2004-01-01
Methods used to project risks in low-Earth orbit are of questionable merit for exploration missions because of the limited radiobiology data and knowledge of galactic cosmic ray (GCR) heavy ions, which causes estimates of the risk of late effects to be highly uncertain. Risk projections involve a product of many biological and physical factors, each of which has a differential range of uncertainty due to lack of data and knowledge. Using the linear-additivity model for radiation risks, we use Monte-Carlo sampling from subjective uncertainty distributions in each factor to obtain an estimate of the overall uncertainty in risk projections. The resulting methodology is applied to several human space exploration mission scenarios including a deep space outpost and Mars missions of duration of 360, 660, and 1000 days. The major results are the quantification of the uncertainties in current risk estimates, the identification of factors that dominate risk projection uncertainties, and the development of a method to quantify candidate approaches to reduce uncertainties or mitigate risks. The large uncertainties in GCR risk projections lead to probability distributions of risk that mask any potential risk reduction using the "optimization" of shielding materials or configurations. In contrast, the design of shielding optimization approaches for solar particle events and trapped protons can be made at this time and promising technologies can be shown to have merit using our approach. The methods used also make it possible to express risk management objectives in terms of quantitative metrics, e.g., the number of days in space without exceeding a given risk level within well-defined confidence limits. Published by Elsevier Ltd on behalf of COSPAR.
Scinicariello, Franco; Portier, Christopher
2016-03-01
Non-cancer risk assessment traditionally assumes a threshold of effect, below which there is a negligible risk of an adverse effect. The Agency for Toxic Substances and Disease Registry derives health-based guidance values known as Minimal Risk Levels (MRLs) as estimates of the toxicity threshold for non-carcinogens. Although the definition of an MRL, as well as EPA reference dose values (RfD and RfC), is a level that corresponds to "negligible risk," they represent daily exposure doses or concentrations, not risks. We present a new approach to calculate the risk at exposure to specific doses for chemical mixtures, the assumption in this approach is to assign de minimis risk at the MRL. The assigned risk enables the estimation of parameters in an exponential model, providing a complete dose-response curve for each compound from the chosen point of departure to zero. We estimated parameters for 27 chemicals. The value of k, which determines the shape of the dose-response curve, was moderately insensitive to the choice of the risk at the MRL. The approach presented here allows for the calculation of a risk from a single substance or the combined risk from multiple chemical exposures in a community. The methodology is applicable from point of departure data derived from quantal data, such as data from benchmark dose analyses or from data that can be transformed into probabilities, such as lowest-observed-adverse-effect level. The individual risks are used to calculate risk ratios that can facilitate comparison and cost-benefit analyses of environmental contamination control strategies.
Analysis of a probability-based SATCOM situational awareness model for parameter estimation
NASA Astrophysics Data System (ADS)
Martin, Todd W.; Chang, Kuo-Chu; Tian, Xin; Chen, Genshe
2016-05-01
Emerging satellite communication (SATCOM) systems are envisioned to incorporate advanced capabilities for dynamically adapting link and network configurations to meet user performance needs. These advanced capabilities require an understanding of the operating environment as well as the potential outcomes of adaptation decisions. A SATCOM situational awareness and decision-making approach is needed that represents the cause and effect linkage of relevant phenomenology and operating conditions on link performance. Similarly, the model must enable a corresponding diagnostic capability that allows SATCOM payload managers to assess likely causes of observed effects. Prior work demonstrated the ability to use a probabilistic reasoning model for a SATCOM situational awareness model. It provided the theoretical basis and demonstrated the ability to realize such a model. This paper presents an analysis of the probabilistic reasoning approach in the context of its ability to be used for diagnostic purposes. A quantitative assessment is presented to demonstrate the impact of uncertainty on estimation accuracy for several key parameters. The paper also discusses how the results could be used by a higher-level reasoning process to evaluate likely causes of performance shortfalls such as atmospheric conditions, pointing errors, and jamming.
Estimating the re-identification risk of clinical data sets
2012-01-01
Background De-identification is a common way to protect patient privacy when disclosing clinical data for secondary purposes, such as research. One type of attack that de-identification protects against is linking the disclosed patient data with public and semi-public registries. Uniqueness is a commonly used measure of re-identification risk under this attack. If uniqueness can be measured accurately then the risk from this kind of attack can be managed. In practice, it is often not possible to measure uniqueness directly, therefore it must be estimated. Methods We evaluated the accuracy of uniqueness estimators on clinically relevant data sets. Four candidate estimators were identified because they were evaluated in the past and found to have good accuracy or because they were new and not evaluated comparatively before: the Zayatz estimator, slide negative binomial estimator, Pitman’s estimator, and mu-argus. A Monte Carlo simulation was performed to evaluate the uniqueness estimators on six clinically relevant data sets. We varied the sampling fraction and the uniqueness in the population (the value being estimated). The median relative error and inter-quartile range of the uniqueness estimates was measured across 1000 runs. Results There was no single estimator that performed well across all of the conditions. We developed a decision rule which selected between the Pitman, slide negative binomial and Zayatz estimators depending on the sampling fraction and the difference between estimates. This decision rule had the best consistent median relative error across multiple conditions and data sets. Conclusion This study identified an accurate decision rule that can be used by health privacy researchers and disclosure control professionals to estimate uniqueness in clinical data sets. The decision rule provides a reliable way to measure re-identification risk. PMID:22776564
ERIC Educational Resources Information Center
Green, Dido; Lingam, Raghu; Mattocks, Calum; Riddoch, Chris; Ness, Andy; Emond, Alan
2011-01-01
The aim of the current study was to test the hypothesis that children with probable Developmental Coordination Disorder have an increased risk of reduced moderate to vigorous physical activity (MVPA), using data from a large population based study. Prospectively collected data from 4331 children (boys = 2065, girls = 2266) who had completed motor…
These model-based estimates use two surveys, the Behavioral Risk Factor Surveillance System (BRFSS) and the National Health Interview Survey (NHIS). The two surveys are combined using novel statistical methodology.
Estimating cancer risks to adults undergoing body CT examinations.
Huda, Walter; He, Wenjun
2012-06-01
The purpose of the study is to estimate cancer risks from the amount of radiation used to perform body computed tomography (CT) examination. The ImPACT CT Patient Dosimetry Calculator was used to compute values of organ doses for adult body CT examinations. The radiation used to perform each examination was quantified by the dose-length product (DLP). Patient organ doses were converted into corresponding age and sex dependent cancer risks using data from BEIR VII. Results are presented for cancer risks per unit DLP and unit effective dose for 11 sensitive organs, as well as estimates of the contribution from 'other organs'. For patients who differ from a standard sized adult, correction factors based on the patient weight and antero-posterior dimension are provided to adjust organ doses and the corresponding risks. At constant incident radiation intensity, for CT examinations that include the chest, risks for females are markedly higher than those for males, whereas for examinations that include the pelvis, risks in males were slightly higher than those in females. In abdominal CT scans, risks for males and female patients are very similar. For abdominal CT scans, increasing the patient age from 20 to 80 resulted in a reduction in patient risks of nearly a factor of 5. The average cancer risk for chest/abdomen/pelvis CT examinations was ∼26 % higher than the cancer risk caused by 'sensitive organs'. Doses and radiation risks in 80 kg adults were ∼10 % lower than those in 70 kg patients. Cancer risks in body CT can be estimated from the examination DLP by accounting for sex, age, as well as patient physical characteristics.
NASA Technical Reports Server (NTRS)
Chappell, Lori J.; Cucinotta, Francis A.
2011-01-01
Radiation risks are estimated in a competing risk formalism where age or time after exposure estimates of increased risks for cancer and circulatory diseases are folded with a probability to survive to a given age. The survival function, also called the life-table, changes with calendar year, gender, smoking status and other demographic variables. An outstanding problem in risk estimation is the method of risk transfer between exposed populations and a second population where risks are to be estimated. Approaches used to transfer risks are based on: 1) Multiplicative risk transfer models -proportional to background disease rates. 2) Additive risk transfer model -risks independent of background rates. In addition, a Mixture model is often considered where the multiplicative and additive transfer assumptions are given weighted contributions. We studied the influence of the survival probability on the risk of exposure induced cancer and circulatory disease morbidity and mortality in the Multiplicative transfer model and the Mixture model. Risks for never-smokers (NS) compared to the average U.S. population are estimated to be reduced between 30% and 60% dependent on model assumptions. Lung cancer is the major contributor to the reduction for NS, with additional contributions from circulatory diseases and cancers of the stomach, liver, bladder, oral cavity, esophagus, colon, a portion of the solid cancer remainder, and leukemia. Greater improvements in risk estimates for NS s are possible, and would be dependent on improved understanding of risk transfer models, and elucidating the role of space radiation on the various stages of disease formation (e.g. initiation, promotion, and progression).
NASA Astrophysics Data System (ADS)
Maier-Paape, Stanislaus; Wanner, Thomas
This paper is the first in a series of two papers addressing the phenomenon of spinodal decomposition for the Cahn-Hilliard equation
Estimating and Mapping the Population at Risk of Sleeping Sickness
Franco, José R.; Paone, Massimo; Diarra, Abdoulaye; Ruiz-Postigo, José Antonio; Fèvre, Eric M.; Mattioli, Raffaele C.; Jannin, Jean G.
2012-01-01
Background Human African trypanosomiasis (HAT), also known as sleeping sickness, persists as a public health problem in several sub-Saharan countries. Evidence-based, spatially explicit estimates of population at risk are needed to inform planning and implementation of field interventions, monitor disease trends, raise awareness and support advocacy. Comprehensive, geo-referenced epidemiological records from HAT-affected countries were combined with human population layers to map five categories of risk, ranging from “very high” to “very low,” and to estimate the corresponding at-risk population. Results Approximately 70 million people distributed over a surface of 1.55 million km2 are estimated to be at different levels of risk of contracting HAT. Trypanosoma brucei gambiense accounts for 82.2% of the population at risk, the remaining 17.8% being at risk of infection from T. b. rhodesiense. Twenty-one million people live in areas classified as moderate to very high risk, where more than 1 HAT case per 10,000 inhabitants per annum is reported. Discussion Updated estimates of the population at risk of sleeping sickness were made, based on quantitative information on the reported cases and the geographic distribution of human population. Due to substantial methodological differences, it is not possible to make direct comparisons with previous figures for at-risk population. By contrast, it will be possible to explore trends in the future. The presented maps of different HAT risk levels will help to develop site-specific strategies for control and surveillance, and to monitor progress achieved by ongoing efforts aimed at the elimination of sleeping sickness. PMID:23145192
NASA Astrophysics Data System (ADS)
Kim, Dong Hyeok; Lee, Ouk Sub; Kim, Hong Min; Choi, Hye Bin
2008-11-01
A modified Split Hopkinson Pressure Bar technique with aluminum pressure bars and a pulse shaper technique to achieve a closer impedance match between the pressure bars and the specimen materials such as hot temperature degraded POM (Poly Oxy Methylene) and PP (Poly Propylene). The more distinguishable experimental signals were obtained to evaluate the more accurate dynamic deformation behavior of materials under a high strain rate loading condition. A pulse shaping technique is introduced to reduce the non-equilibrium on the dynamic material response by modulation of the incident wave during a short period of test. This increases the rise time of the incident pulse in the SHPB experiment. For the dynamic stress strain curve obtained from SHPB experiment, the Johnson-Cook model is applied as a constitutive equation. The applicability of this constitutive equation is verified by using the probabilistic reliability estimation method. Two reliability methodologies such as the FORM and the SORM have been proposed. The limit state function(LSF) includes the Johnson-Cook model and applied stresses. The LSF in this study allows more statistical flexibility on the yield stress than a paper published before. It is found that the failure probability estimated by using the SORM is more reliable than those of the FORM/ It is also noted that the failure probability increases with increase of the applied stress. Moreover, it is also found that the parameters of Johnson-Cook model such as A and n, and the applied stress are found to affect the failure probability more severely than the other random variables according to the sensitivity analysis.
Sun, Pengfei; Qin, Jun
2017-02-01
In this paper, a two-stage dual tree complex wavelet packet transform (DTCWPT) based speech enhancement algorithm has been proposed, in which a speech presence probability (SPP) estimator and a generalized minimum mean squared error (MMSE) estimator are developed. To overcome the drawback of signal distortions caused by down sampling of wavelet packet transform (WPT), a two-stage analytic decomposition concatenating undecimated wavelet packet transform (UWPT) and decimated WPT is employed. An SPP estimator in the DTCWPT domain is derived based on a generalized Gamma distribution of speech, and Gaussian noise assumption. The validation results show that the proposed algorithm can obtain enhanced perceptual evaluation of speech quality (PESQ), and segmental signal-to-noise ratio (SegSNR) at low signal-to-noise ratio (SNR) nonstationary noise, compared with four other state-of-the-art speech enhancement algorithms, including optimally modified log-spectral amplitude (OM-LSA), soft masking using a posteriori SNR uncertainty (SMPO), a posteriori SPP based MMSE estimation (MMSE-SPP), and adaptive Bayesian wavelet thresholding (BWT).
Gronewold, Andrew D; Wolpert, Robert L
2008-07-01
Most probable number (MPN) and colony-forming-unit (CFU) estimates of fecal coliform bacteria concentration are common measures of water quality in coastal shellfish harvesting and recreational waters. Estimating procedures for MPN and CFU have intrinsic variability and are subject to additional uncertainty arising from minor variations in experimental protocol. It has been observed empirically that the standard multiple-tube fermentation (MTF) decimal dilution analysis MPN procedure is more variable than the membrane filtration CFU procedure, and that MTF-derived MPN estimates are somewhat higher on average than CFU estimates, on split samples from the same water bodies. We construct a probabilistic model that provides a clear theoretical explanation for the variability in, and discrepancy between, MPN and CFU measurements. We then compare our model to water quality samples analyzed using both MPN and CFU procedures, and find that the (often large) observed differences between MPN and CFU values for the same water body are well within the ranges predicted by our probabilistic model. Our results indicate that MPN and CFU intra-sample variability does not stem from human error or laboratory procedure variability, but is instead a simple consequence of the probabilistic basis for calculating the MPN. These results demonstrate how probabilistic models can be used to compare samples from different analytical procedures, and to determine whether transitions from one procedure to another are likely to cause a change in quality-based management decisions.
NASA Astrophysics Data System (ADS)
Vio, R.; Andreani, P.
2016-05-01
The reliable detection of weak signals is a critical issue in many astronomical contexts and may have severe consequences for determining number counts and luminosity functions, but also for optimizing the use of telescope time in follow-up observations. Because of its optimal properties, one of the most popular and widely-used detection technique is the matched filter (MF). This is a linear filter designed to maximise the detectability of a signal of known structure that is buried in additive Gaussian random noise. In this work we show that in the very common situation where the number and position of the searched signals within a data sequence (e.g. an emission line in a spectrum) or an image (e.g. a point-source in an interferometric map) are unknown, this technique, when applied in its standard form, may severely underestimate the probability of false detection. This is because the correct use of the MF relies upon a priori knowledge of the position of the signal of interest. In the absence of this information, the statistical significance of features that are actually noise is overestimated and detections claimed that are actually spurious. For this reason, we present an alternative method of computing the probability of false detection that is based on the probability density function (PDF) of the peaks of a random field. It is able to provide a correct estimate of the probability of false detection for the one-, two- and three-dimensional case. We apply this technique to a real two-dimensional interferometric map obtained with ALMA.
Park, Dong-Uk; Colt, Joanne S; Baris, Dalsu; Schwenn, Molly; Karagas, Margaret R; Armenti, Karla R; Johnson, Alison; Silverman, Debra T; Stewart, Patricia A
2014-01-01
We describe an approach for estimating the probability that study subjects were exposed to metalworking fluids (MWFs) in a population-based case-control study of bladder cancer. Study subject reports on the frequency of machining and use of specific MWFs (straight, soluble, and synthetic/semi-synthetic) were used to estimate exposure probability when available. Those reports also were used to develop estimates for job groups, which were then applied to jobs without MWF reports. Estimates using both cases and controls and controls only were developed. The prevalence of machining varied substantially across job groups (0.1->0.9%), with the greatest percentage of jobs that machined being reported by machinists and tool and die workers. Reports of straight and soluble MWF use were fairly consistent across job groups (generally 50-70%). Synthetic MWF use was lower (13-45%). There was little difference in reports by cases and controls vs. controls only. Approximately, 1% of the entire study population was assessed as definitely exposed to straight or soluble fluids in contrast to 0.2% definitely exposed to synthetic/semi-synthetics. A comparison between the reported use of the MWFs and U.S. production levels found high correlations (r generally >0.7). Overall, the method described here is likely to have provided a systematic and reliable ranking that better reflects the variability of exposure to three types of MWFs than approaches applied in the past. [Supplementary materials are available for this article. Go to the publisher's online edition of Journal of Occupational and Environmental Hygiene for the following free supplemental resources: a list of keywords in the occupational histories that were used to link study subjects to the metalworking fluids (MWFs) modules; recommendations from the literature on selection of MWFs based on type of machining operation, the metal being machined and decade; popular additives to MWFs; the number and proportion of controls who
Non-parametric estimation of relative risk in survival and associated tests.
Wakounig, Samo; Heinze, Georg; Schemper, Michael
2015-12-01
We extend the Tarone and Ware scheme of weighted log-rank tests to cover the associated weighted Mantel-Haenszel estimators of relative risk. Weighting functions previously employed are critically reviewed. The notion of an average hazard ratio is defined and its connection to the effect size measure P(Y > X) is emphasized. The connection makes estimation of P(Y > X) possible also under censoring. Two members of the extended Tarone-Ware scheme accomplish the estimation of intuitively interpretable average hazard ratios, also under censoring and time-varying relative risk which is achieved by an inverse probability of censoring weighting. The empirical properties of the members of the extended Tarone-Ware scheme are demonstrated by a Monte Carlo study. The differential role of the weighting functions considered is illustrated by a comparative analysis of four real data sets.
Eash, David A.; Barnes, Kimberlee K.; Veilleux, Andrea G.
2013-01-01
A statewide study was performed to develop regional regression equations for estimating selected annual exceedance-probability statistics for ungaged stream sites in Iowa. The study area comprises streamgages located within Iowa and 50 miles beyond the State’s borders. Annual exceedance-probability estimates were computed for 518 streamgages by using the expected moments algorithm to fit a Pearson Type III distribution to the logarithms of annual peak discharges for each streamgage using annual peak-discharge data through 2010. The estimation of the selected statistics included a Bayesian weighted least-squares/generalized least-squares regression analysis to update regional skew coefficients for the 518 streamgages. Low-outlier and historic information were incorporated into the annual exceedance-probability analyses, and a generalized Grubbs-Beck test was used to detect multiple potentially influential low flows. Also, geographic information system software was used to measure 59 selected basin characteristics for each streamgage. Regional regression analysis, using generalized least-squares regression, was used to develop a set of equations for each flood region in Iowa for estimating discharges for ungaged stream sites with 50-, 20-, 10-, 4-, 2-, 1-, 0.5-, and 0.2-percent annual exceedance probabilities, which are equivalent to annual flood-frequency recurrence intervals of 2, 5, 10, 25, 50, 100, 200, and 500 years, respectively. A total of 394 streamgages were included in the development of regional regression equations for three flood regions (regions 1, 2, and 3) that were defined for Iowa based on landform regions and soil regions. Average standard errors of prediction range from 31.8 to 45.2 percent for flood region 1, 19.4 to 46.8 percent for flood region 2, and 26.5 to 43.1 percent for flood region 3. The pseudo coefficients of determination for the generalized least-squares equations range from 90.8 to 96.2 percent for flood region 1, 91.5 to 97
Handel, Ian G.; de C. Bronsvoort, Barend M.; Forbes, John F.; Woolhouse, Mark E. J.
2011-01-01
Current post-epidemic sero-surveillance uses random selection of animal holdings. A better strategy may be to estimate the benefits gained by sampling each farm and use this to target selection. In this study we estimate the probability of undiscovered infection for sheep farms in Devon after the 2001 foot-and-mouth disease outbreak using the combination of a previously published model of daily infection risk and a simple model of probability of discovery of infection during the outbreak. This allows comparison of the system sensitivity (ability to detect infection in the area) of arbitrary, random sampling compared to risk-targeted selection across a full range of sampling budgets. We show that it is possible to achieve 95% system sensitivity by sampling, on average, 945 farms with random sampling and 184 farms with risk-targeted sampling. We also examine the effect of ordering samples by risk to expedite return to a disease-free status. Risk ordering the sampling process results in detection of positive farms, if present, 15.6 days sooner than with randomly ordered sampling, assuming 50 farms are tested per day. PMID:21674022
Cai, T; Perletti, G; Meacci, F; Magri, V; Verze, P; Palmieri, A; Mazzoli, S; Santi, R; Nesi, G; Mirone, V; Bartoletti, R
2016-03-01
In this study, we aimed to investigate the clearance of type-specific genital human papillomavirus (HPV) infection in heterosexual, non-HPV-vaccinated males whose female partners were positive to HPV DNA tests. All consecutive men attending the same sexually transmitted diseases (STD) centre between January 2005 and December 2006 were considered for this study. All subjects (n = 1009) underwent a urologic visit and microbiological tests on first void, midstream urine and total ejaculate samples. One hundred and five patients were positive for HPV DNA (10.4 %; mean age: 34.8 ± 5.8 years) and consented to clinical examination and molecular diagnostic assays for HPV detection scheduled every 6 months (median surveillance period of 53.2 months). HPV genotypes were classified as high risk, probable high risk and low risk. HPV-positive samples which did not hybridise with any of the type-specific probes were referred to as positive non-genotypeable. At enrollment, the distribution of HPV genotypes was as follows: high-risk HPV (n = 37), probable high-risk HPV (n = 6), low-risk HPV (n = 23) and non-genotypeable HPV (n = 39). A high HPV genotype concordance between stable sexual partners emerged (kappa = 0.92; p < 0.001). At the end of the study, 71/105 (67.6 %) subjects were negative for HPV (mean virus clearance time: 24.3 months). With regard to the HPV genotype, virus clearance was observed in 14/37 (37.8 %) high-risk HPV cases, 6/6 (100 %) probable high-risk HPV cases, 20/23 (86.9 %) low-risk HPV cases and 31/39 (79.5 %) non-genotypeable cases. The high-risk HPV genotypes showed the lowest rate and probability of viral clearance (p < 0.001). In our series, high-risk HPV infections were more likely to persist over time when compared with other HPV genotypes.
Moser, Barry Kurt; Halabi, Susan
2012-01-13
The analysis of case-control studies with matched controls per case is well documented in the medical literature. Of primary interest is the estimation of the relative risk of disease. Matched case-control studies fall into two scenarios: the probability of exposure is constant within each of the case and control groups, or the probability of exposure varies within each group. Numerous estimation procedures have been developed for both scenarios. Often these procedures are developed under the rare disease assumption, where the relative risk of disease is approximated by the odds ratio. In this paper, without making the rare disease assumption, we develop consistent estimators of the relative risk of disease for both scenarios. Exact derivations of the relative risk of disease are provided. Estimators, confidence intervals, and test statistics for the relative risk of disease are developed. We then make the following observations based on extensive simulations. First, our estimators are as close or closer to the relative risk of disease than other estimators. Second, our estimators produce mean square errors for the relative risk of disease that are as good as or better than these other estimators. Third, our confidence intervals provide accurate coverage probabilities. Therefore, these new estimators, confidence intervals, and test statistics can be used to either estimate or test the relative risk of disease in matched case-control studies.
NASA Astrophysics Data System (ADS)
Jaynes, E. T.; Bretthorst, G. Larry
2003-04-01
Foreword; Preface; Part I. Principles and Elementary Applications: 1. Plausible reasoning; 2. The quantitative rules; 3. Elementary sampling theory; 4. Elementary hypothesis testing; 5. Queer uses for probability theory; 6. Elementary parameter estimation; 7. The central, Gaussian or normal distribution; 8. Sufficiency, ancillarity, and all that; 9. Repetitive experiments, probability and frequency; 10. Physics of 'random experiments'; Part II. Advanced Applications: 11. Discrete prior probabilities, the entropy principle; 12. Ignorance priors and transformation groups; 13. Decision theory: historical background; 14. Simple applications of decision theory; 15. Paradoxes of probability theory; 16. Orthodox methods: historical background; 17. Principles and pathology of orthodox statistics; 18. The Ap distribution and rule of succession; 19. Physical measurements; 20. Model comparison; 21. Outliers and robustness; 22. Introduction to communication theory; References; Appendix A. Other approaches to probability theory; Appendix B. Mathematical formalities and style; Appendix C. Convolutions and cumulants.
Jenkins, Rachel; Othieno, Caleb; Omollo, Raymond; Ongeri, Linnet; Sifuna, Peter; Mboroki, James Kingora; Kiima, David; Ogutu, Bernhards
2015-01-01
This study aimed to assess the prevalence of probable post-traumatic stress disorder (PTSD), and its associated risk factors in a general household population in Kenya. Data were drawn from a cross-sectional household survey of mental disorders and their associated risk factors. The participants received a structured epidemiological assessment of common mental disorders, and symptoms of PTSD, accompanied by additional sections on socio-demographic data, life events, social networks, social supports, disability/activities of daily living, quality of life, use of health services, and service use. The study found that 48% had experienced a severe trauma, and an overall prevalence rate of 10.6% of probable PTSD, defined as a score of six or more on the trauma screening questionnaire (TSQ). The conditional probability of PTSD was 0.26. Risk factors include being female, single, self-employed, having experienced recent life events, having a common mental disorder (CMD)and living in an institution before age 16. The study indicates that probable PTSD is prevalent in this rural area of Kenya. The findings are relevant for the training of front line health workers, their support and supervision, for health management information systems, and for mental health promotion in state boarding schools. PMID:26516877
NASA Astrophysics Data System (ADS)
Ettinger, Susanne; Mounaud, Loïc; Magill, Christina; Yao-Lafourcade, Anne-Françoise; Thouret, Jean-Claude; Manville, Vern; Negulescu, Caterina; Zuccaro, Giulio; De Gregorio, Daniela; Nardone, Stefano; Uchuchoque, Juan Alexis Luque; Arguedas, Anita; Macedo, Luisa; Manrique Llerena, Nélida
2016-10-01
The focus of this study is an analysis of building vulnerability through investigating impacts from the 8 February 2013 flash flood event along the Avenida Venezuela channel in the city of Arequipa, Peru. On this day, 124.5 mm of rain fell within 3 h (monthly mean: 29.3 mm) triggering a flash flood that inundated at least 0.4 km2 of urban settlements along the channel, affecting more than 280 buildings, 23 of a total of 53 bridges (pedestrian, vehicle and railway), and leading to the partial collapse of sections of the main road, paralyzing central parts of the city for more than one week. This study assesses the aspects of building design and site specific environmental characteristics that render a building vulnerable by considering the example of a flash flood event in February 2013. A statistical methodology is developed that enables estimation of damage probability for buildings. The applied method uses observed inundation height as a hazard proxy in areas where more detailed hydrodynamic modeling data is not available. Building design and site-specific environmental conditions determine the physical vulnerability. The mathematical approach considers both physical vulnerability and hazard related parameters and helps to reduce uncertainty in the determination of descriptive parameters, parameter interdependency and respective contributions to damage. This study aims to (1) enable the estimation of damage probability for a certain hazard intensity, and (2) obtain data to visualize variations in damage susceptibility for buildings in flood prone areas. Data collection is based on a post-flood event field survey and the analysis of high (sub-metric) spatial resolution images (Pléiades 2012, 2013). An inventory of 30 city blocks was collated in a GIS database in order to estimate the physical vulnerability of buildings. As many as 1103 buildings were surveyed along the affected drainage and 898 buildings were included in the statistical analysis. Univariate and
Cole, Stephen R; Lau, Bryan; Eron, Joseph J; Brookhart, M Alan; Kitahata, Mari M; Martin, Jeffrey N; Mathews, William C; Mugavero, Michael J
2015-02-15
There are few published examples of absolute risk estimated from epidemiologic data subject to censoring and competing risks with adjustment for multiple confounders. We present an example estimating the effect of injection drug use on 6-year risk of acquired immunodeficiency syndrome (AIDS) after initiation of combination antiretroviral therapy between 1998 and 2012 in an 8-site US cohort study with death before AIDS as a competing risk. We estimate the risk standardized to the total study sample by combining inverse probability weights with the cumulative incidence function; estimates of precision are obtained by bootstrap. In 7,182 patients (83% male, 33% African American, median age of 38 years), we observed 6-year standardized AIDS risks of 16.75% among 1,143 injection drug users and 12.08% among 6,039 nonusers, yielding a standardized risk difference of 4.68 (95% confidence interval: 1.27, 8.08) and a standardized risk ratio of 1.39 (95% confidence interval: 1.12, 1.72). Results may be sensitive to the assumptions of exposure-version irrelevance, no measurement bias, and no unmeasured confounding. These limitations suggest that results be replicated with refined measurements of injection drug use. Nevertheless, estimating the standardized risk difference and ratio is straightforward, and injection drug use appears to increase the risk of AIDS.
Methods to Develop Inhalation Cancer Risk Estimates for ...
This document summarizes the approaches and rationale for the technical and scientific considerations used to derive inhalation cancer risks for emissions of chromium and nickel compounds from electric utility steam generating units. The purpose of this document is to discuss the methods used to develop inhalation cancer risk estimates associated with emissions of chromium and nickel compounds from coal- and oil-fired electric utility steam generating units (EGUs) in support of EPA's recently proposed Air Toxics Rule.
Studies on the extended Techa river cohort: cancer risk estimation
Kossenko, M M.; Preston, D L.; Krestinina, L Y.; Degteva, M O.; Startsev, N V.; Thomas, T; Vyushkova, O V.; Anspaugh, L R.; Napier, Bruce A. ); Kozheurov, V P.; Ron, E; Akleyev, A V.
2001-12-01
Initial population-based studies of riverside residents were begun in the late 1950s and in 1967 a systematic effort was undertaken to develop a well-defined fixed cohort of Techa river residents, to carry out ongoing mortality and (limited) clinical follow-up of this cohort, and to provide individualized dose estimates for cohort members. Over the past decade, extensive efforts have been made to refine the cohort definition and improve both the follow-up and dosimetry data. Analyses of the Techa river cohort can provide useful quantitative estimates of the effects of low dose rate, chronic external and internal exposures on cancer mortality and incidence and non-cancer mortality rates. These risk estimates complement quantitative risk estimates for acute exposures based on the atomic bomb survivors and chronic exposure risk estimates from worker studies, including Mayak workers and other groups with occupational radiation exposures. As the dosimetry and follow-up are refined it may also be possible to gain useful insights into risks associated with 90Sr exposures.
Prah, Philip; Hickson, Ford; Bonell, Chris; McDaid, Lisa M; Johnson, Anne M; Wayal, Sonali; Clifton, Soazig; Sonnenberg, Pam; Nardone, Anthony; Erens, Bob; Copas, Andrew J; Riddell, Julie; Weatherburn, Peter; Mercer, Catherine H
2016-01-01
Objective To examine sociodemographic and behavioural differences between men who have sex with men (MSM) participating in recent UK convenience surveys and a national probability sample survey. Methods We compared 148 MSM aged 18–64 years interviewed for Britain's third National Survey of Sexual Attitudes and Lifestyles (Natsal-3) undertaken in 2010–2012, with men in the same age range participating in contemporaneous convenience surveys of MSM: 15 500 British resident men in the European MSM Internet Survey (EMIS); 797 in the London Gay Men's Sexual Health Survey; and 1234 in Scotland's Gay Men's Sexual Health Survey. Analyses compared men reporting at least one male sexual partner (past year) on similarly worded questions and multivariable analyses accounted for sociodemographic differences between the surveys. Results MSM in convenience surveys were younger and better educated than MSM in Natsal-3, and a larger proportion identified as gay (85%–95% vs 62%). Partner numbers were higher and same-sex anal sex more common in convenience surveys. Unprotected anal intercourse was more commonly reported in EMIS. Compared with Natsal-3, MSM in convenience surveys were more likely to report gonorrhoea diagnoses and HIV testing (both past year). Differences between the samples were reduced when restricting analysis to gay-identifying MSM. Conclusions National probability surveys better reflect the population of MSM but are limited by their smaller samples of MSM. Convenience surveys recruit larger samples of MSM but tend to over-represent MSM identifying as gay and reporting more sexual risk behaviours. Because both sampling strategies have strengths and weaknesses, methods are needed to triangulate data from probability and convenience surveys. PMID:26965869
Wang, Yuan; Gao, Ying; Battsend, Munkhzul; Chen, Kexin; Lu, Wenli; Wang, Yaogang
2014-11-01
The optimal approach regarding breast cancer screening for Chinese women is unclear due to the relative low incidence rate. A risk assessment tool may be useful for selection of high-risk subsets of population for mammography screening in low-incidence and resource-limited developing country. The odd ratios for six main risk factors of breast cancer were pooled by review manager after a systematic research of literature. Health risk appraisal (HRA) model was developed to predict an individual's risk of developing breast cancer in the next 5 years from current age. The performance of this HRA model was assessed based on a first-round screening database. Estimated risk of breast cancer increased with age. Increases in the 5-year risk of developing breast cancer were found with the existence of any of included risk factors. When individuals who had risk above median risk (3.3‰) were selected from the validation database, the sensitivity is 60.0% and the specificity is 47.8%. The unweighted area under the curve (AUC) was 0.64 (95% CI = 0.50-0.78). The risk-prediction model reported in this article is based on a combination of risk factors and shows good overall predictive power, but it is still weak at predicting which particular women will develop the disease. It would be very helpful for the improvement of a current model if more population-based prospective follow-up studies were used for the validation.
NASA Astrophysics Data System (ADS)
Karwowski, Damian; Domański, Marek
2016-01-01
An improved context-based adaptive binary arithmetic coding (CABAC) is presented. The idea for the improvement is to use a more accurate mechanism for estimation of symbol probabilities in the standard CABAC algorithm. The authors' proposal of such a mechanism is based on the context-tree weighting technique. In the framework of a high-efficiency video coding (HEVC) video encoder, the improved CABAC allows 0.7% to 4.5% bitrate saving compared to the original CABAC algorithm. The application of the proposed algorithm marginally affects the complexity of HEVC video encoder, but the complexity of video decoder increases by 32% to 38%. In order to decrease the complexity of video decoding, a new tool has been proposed for the improved CABAC that enables scaling of the decoder complexity. Experiments show that this tool gives 5% to 7.5% reduction of the decoding time while still maintaining high efficiency in the data compression.
Estimating transport fatality risk from past accident data.
Evans, Andrew W
2003-07-01
This paper examines the statistical properties of estimates of fatal accident rates, mean fatalities per accident, and fatality rates when these estimates are based on past accident data. The statistical properties are illustrated by two long-term transport fatal accident datasets from Great Britain, the principal one for railways and the other for roads, chosen to provide a statistical contrast. In both modes, the accident rates have fallen substantially over the long term. Two statistical estimates of current accident and fatality rates are presented for each dataset, one based only on recent data and the other based on estimates of long-term trends. The trend-based estimate is preferred for train accidents because this makes maximum use of the limited and variable data; the recent data are preferred for road accidents because this avoids unnecessary dependence on modelling the trends. For train accidents, the estimated fatality rate based on past accidents is compared with an estimate produced by the railway industry using a risk model. The statistical estimate is less than half the industry's estimate, and the paper concludes that the statistical estimate is to be preferred.
Sensitivity of risk estimates to wildlife bioaccumulation factors in ecological risk assessment
Karustis, C.G.; Brewer, R.A.
1995-12-31
The concept of conservatism in risk assessment is well established. However, overly conservative assumptions may result in risk estimates that incorrectly predict remediation goals. Therefore, realistic assumptions should be applied in risk assessment whenever possible. A sensitivity analysis was performed on conservative (i.e. bioaccumulation factor = 1) and scientifically-derived wildlife bioaccumulation factors (BAFs) utilized to calculate risks during a terrestrial ecological risk assessment (ERA). In the first approach, 100% bioaccumulation of contaminants was assumed to estimate the transfer of contaminants through the terrestrial food chain. In the second approach, scientifically-derived BAFs were selected from the literature. For one of the measurement species selected, total risks calculated during the first approach were higher than those calculated during the second approach by two orders of magnitude. However, potential risks due to individual contaminants were not necessarily higher using the conservative approach. Potential risk due to contaminants with low actual bioaccumulation were exaggerated while potential risks due to contaminants with greater than 100% bioaccumulation were underestimated. Therefore, the use of a default of 100% bioaccumulation (BAF = 1) for all contaminants encountered during an ERA could result in cases where contaminants are incorrectly identified as risk drivers, and the calculation of incorrect ecological risk-based cleanup goals. The authors suggest using site-specific or literature-derived BAFs whenever possible and realistic BAF estimates, based upon factors such as log K{sub ow}, when BAFs are unavailable.
Reconstruction of financial networks for robust estimation of systemic risk
NASA Astrophysics Data System (ADS)
Mastromatteo, Iacopo; Zarinelli, Elia; Marsili, Matteo
2012-03-01
In this paper we estimate the propagation of liquidity shocks through interbank markets when the information about the underlying credit network is incomplete. We show that techniques such as maximum entropy currently used to reconstruct credit networks severely underestimate the risk of contagion by assuming a trivial (fully connected) topology, a type of network structure which can be very different from the one empirically observed. We propose an efficient message-passing algorithm to explore the space of possible network structures and show that a correct estimation of the network degree of connectedness leads to more reliable estimations for systemic risk. Such an algorithm is also able to produce maximally fragile structures, providing a practical upper bound for the risk of contagion when the actual network structure is unknown. We test our algorithm on ensembles of synthetic data encoding some features of real financial networks (sparsity and heterogeneity), finding that more accurate estimations of risk can be achieved. Finally we find that this algorithm can be used to control the amount of information that regulators need to require from banks in order to sufficiently constrain the reconstruction of financial networks.
Estimates of endemic waterborne risks from community-intervention studies.
Calderon, Rebecca L; Craun, Gunther F
2006-01-01
The nature and magnitude of endemic waterborne disease are not well characterized in the United States. Epidemiologic studies of various designs can provide an estimate of the waterborne attributable risk along with other types of information. Community drinking water systems frequently improve their operations and may change drinking water treatment and their major source of water. In the United States, many of these treatment changes are the result of regulations promulgated under the Safe Drinking Water Act. A community-intervention study design takes advantage of these "natural" experiments to assess changes in health risks. In this paper, we review the community-intervention studies that have assessed changes in waterborne gastroenteritis risks among immunocompetent populations in industrialized countries. Published results are available from two studies in Australia, one study in the United Kingdom, and one study in the United States. Preliminary results from two other US studies are also available. Although the current information is limited, the risks reported in these community-intervention studies can help inform the national estimate of endemic waterborne gastroenteritis. Information is provided about endemic waterborne risks for unfiltered surface water sources and a groundwater under the influence of surface water. Community-intervention studies with recommended study modifications should be conducted to better estimate the benefits associated with improved drinking water treatment.
Greenland, S
1999-01-01
Epidemiologists, biostatisticians, and health physicists frequently serve as expert consultants to lawyers, courts, and administrators. One of the most common errors committed by experts is to equate, without qualification, the attributable fraction estimated from epidemiologic data to the probability of causation requested by courts and administrators. This error has become so pervasive that it has been incorporated into judicial precedents and legislation. This commentary provides a brief overview of the error and the context in which it arises. PMID:10432900
Neoplastic potential of gastric irradiation. IV. Risk estimates
Griem, M.L.; Justman, J.; Weiss, L.
1984-12-01
No significant tumor increase was found in the initial analysis of patients irradiated for peptic ulcer and followed through 1962. A preliminary study was undertaken 22 years later to estimate the risk of cancer due to gastric irradiation for peptic ulcer disease. A population of 2,049 irradiated patients and 763 medically managed patients has been identified. A relative risk of 3.7 was found for stomach cancer and an initial risk estimate of 5.5 x 10(-6) excess stomach cancers per person rad was calculated. A more complete follow-up is in progress to further elucidate this observation and decrease the ascertainment bias; however, preliminary data are in agreement with the Japanese atomic bomb reports.
Southard, Rodney E.; Veilleux, Andrea G.
2014-01-01
Regression analysis techniques were used to develop a set of equations for rural ungaged stream sites for estimating discharges with 50-, 20-, 10-, 4-, 2-, 1-, 0.5-, and 0.2-percent annual exceedance probabilities, which are equivalent to annual flood-frequency recurrence intervals of 2, 5, 10, 25, 50, 100, 200, and 500 years, respectively. Basin and climatic characteristics were computed using geographic information software and digital geospatial data. A total of 35 characteristics were computed for use in preliminary statewide and regional regression analyses. Annual exceedance-probability discharge estimates were computed for 278 streamgages by using the expected moments algorithm to fit a log-Pearson Type III distribution to the logarithms of annual peak discharges for each streamgage using annual peak-discharge data from water year 1844 to 2012. Low-outlier and historic information were incorporated into the annual exceedance-probability analyses, and a generalized multiple Grubbs-Beck test was used to detect potentially influential low floods. Annual peak flows less than a minimum recordable discharge at a streamgage were incorporated into the at-site station analyses. An updated regional skew coefficient was determined for the State of Missouri using Bayesian weighted least-squares/generalized least squares regression analyses. At-site skew estimates for 108 long-term streamgages with 30 or more years of record and the 35 basin characteristics defined for this study were used to estimate the regional variability in skew. However, a constant generalized-skew value of -0.30 and a mean square error of 0.14 were determined in this study. Previous flood studies indicated that the distinct physical features of the three physiographic provinces have a pronounced effect on the magnitude of flood peaks. Trends in the magnitudes of the residuals from preliminary statewide regression analyses from previous studies confirmed that regional analyses in this study were
Estimation of myocardial volume at risk from CT angiography
NASA Astrophysics Data System (ADS)
Zhu, Liangjia; Gao, Yi; Mohan, Vandana; Stillman, Arthur; Faber, Tracy; Tannenbaum, Allen
2011-03-01
The determination of myocardial volume at risk distal to coronary stenosis provides important information for prognosis and treatment of coronary artery disease. In this paper, we present a novel computational framework for estimating the myocardial volume at risk in computed tomography angiography (CTA) imagery. Initially, epicardial and endocardial surfaces, and coronary arteries are extracted using an active contour method. Then, the extracted coronary arteries are projected onto the epicardial surface, and each point on this surface is associated with its closest coronary artery using the geodesic distance measurement. The likely myocardial region at risk on the epicardial surface caused by a stenosis is approximated by the region in which all its inner points are associated with the sub-branches distal to the stenosis on the coronary artery tree. Finally, the likely myocardial volume at risk is approximated by the volume in between the region at risk on the epicardial surface and its projection on the endocardial surface, which is expected to yield computational savings over risk volume estimation using the entire image volume. Furthermore, we expect increased accuracy since, as compared to prior work using the Euclidean distance, we employ the geodesic distance in this work. The experimental results demonstrate the effectiveness of the proposed approach on pig heart CTA datasets.
Estimating cancer risk from dental cone-beam CT exposures based on skin dosimetry
NASA Astrophysics Data System (ADS)
Pauwels, Ruben; Cockmartin, Lesley; Ivanauskaité, Deimante; Urbonienė, Ausra; Gavala, Sophia; Donta, Catherine; Tsiklakis, Kostas; Jacobs, Reinhilde; Bosmans, Hilde; Bogaerts, Ria; Horner, Keith; SEDENTEXCT Project Consortium, The
2014-07-01
The aim of this study was to measure entrance skin doses on patients undergoing cone-beam computed tomography (CBCT) examinations, to establish conversion factors between skin and organ doses, and to estimate cancer risk from CBCT exposures. 266 patients (age 8-83) were included, involving three imaging centres. CBCT scans were acquired using the SCANORA 3D (Soredex, Tuusula, Finland) and NewTom 9000 (QR, Verona, Italy). Eight thermoluminescent dosimeters were attached to the patient's skin at standardized locations. Using previously published organ dose estimations on various CBCTs with an anthropomorphic phantom, correlation factors to convert skin dose to organ doses were calculated and applied to estimate patient organ doses. The BEIR VII age- and gender-dependent dose-risk model was applied to estimate the lifetime attributable cancer risk. For the SCANORA 3D, average skin doses over the eight locations varied between 484 and 1788 µGy. For the NewTom 9000 the range was between 821 and 1686 µGy for Centre 1 and between 292 and 2325 µGy for Centre 2. Entrance skin dose measurements demonstrated the combined effect of exposure and patient factors on the dose. The lifetime attributable cancer risk, expressed as the probability to develop a radiation-induced cancer, varied between 2.7 per million (age >60) and 9.8 per million (age 8-11) with an average of 6.0 per million. On average, the risk for female patients was 40% higher. The estimated radiation risk was primarily influenced by the age at exposure and the gender, pointing out the continuing need for justification and optimization of CBCT exposures, with a specific focus on children.
Estimating cancer risk from dental cone-beam CT exposures based on skin dosimetry.
Pauwels, Ruben; Cockmartin, Lesley; Ivanauskaité, Deimante; Urbonienė, Ausra; Gavala, Sophia; Donta, Catherine; Tsiklakis, Kostas; Jacobs, Reinhilde; Bosmans, Hilde; Bogaerts, Ria; Horner, Keith
2014-07-21
The aim of this study was to measure entrance skin doses on patients undergoing cone-beam computed tomography (CBCT) examinations, to establish conversion factors between skin and organ doses, and to estimate cancer risk from CBCT exposures. 266 patients (age 8-83) were included, involving three imaging centres. CBCT scans were acquired using the SCANORA 3D (Soredex, Tuusula, Finland) and NewTom 9000 (QR, Verona, Italy). Eight thermoluminescent dosimeters were attached to the patient's skin at standardized locations. Using previously published organ dose estimations on various CBCTs with an anthropomorphic phantom, correlation factors to convert skin dose to organ doses were calculated and applied to estimate patient organ doses. The BEIR VII age- and gender-dependent dose-risk model was applied to estimate the lifetime attributable cancer risk. For the SCANORA 3D, average skin doses over the eight locations varied between 484 and 1788 µGy. For the NewTom 9000 the range was between 821 and 1686 µGy for Centre 1 and between 292 and 2325 µGy for Centre 2. Entrance skin dose measurements demonstrated the combined effect of exposure and patient factors on the dose. The lifetime attributable cancer risk, expressed as the probability to develop a radiation-induced cancer, varied between 2.7 per million (age >60) and 9.8 per million (age 8-11) with an average of 6.0 per million. On average, the risk for female patients was 40% higher. The estimated radiation risk was primarily influenced by the age at exposure and the gender, pointing out the continuing need for justification and optimization of CBCT exposures, with a specific focus on children.
Eichmann, Cordula; Berger, Burkhard; Steinlechner, Martin; Parson, Walther
2005-06-30
Dog DNA-profiling is becoming an important supplementary technology for the investigation of accident and crime, as dogs are intensely integrated in human social life. We investigated 15 highly polymorphic canine STR markers and two sex-related markers of 131 randomly selected dogs from the area around Innsbruck, Tyrol, Austria, which were co-amplified in three PCR multiplex reactions (ZUBECA6, FH2132, FH2087Ua, ZUBECA4, WILMSTF, PEZ15, PEZ6, FH2611, FH2087Ub, FH2054, PEZ12, PEZ2, FH2010, FH2079 and VWF.X). Linkage testing for our set of marker suggested no evidence for linkage between the loci. Heterozygosity (HET), polymorphism information content (PIC) and the probability of identity (P((ID)theoretical), P((ID)unbiased), P((ID)sib)) were calculated for each marker. The HET((exp))-values of the 15 markers lie between 0.6 (VWF.X) and 0.9 (ZUBECA6), P((ID)sib)-values were found to range between 0.49 (VWF.X) and 0.28 (ZUBECA6). Moreover, the P((ID)sib) was computed for sets of loci by sequentially adding single loci to estimate the information content and the usefulness of the selected marker sets for the identification of dogs. The estimated P((ID)sib) value of all 15 markers amounted to 8.5 x 10(-8). The presented estimations turned out to be a helpful approach for a reasonable choice of markers for the individualisation of dogs.
Estimating population health risk from low-level environmental radon
Fisher, D.R.
1980-01-01
Although incidence of respiratory cancer is directly related to inhalation of radon and radon daughters, the magnitude of the actual risk is uncertain for members of the general population exposed for long periods to low-level concentrations. Currently, any such estimate of the risk must rely on data obtained through previous studies of underground-miner populations. Several methods of risk analysis have resulted from these studies. Since the breathing atmospheres, smoking patterns, and physiology are different between miners and the general public, overestimates of lung cancer risk to the latter may have resulted. Strong evidence exists to support the theory of synergistic action between alpha radiation and other agents, and therefore a modified relative risk model was developed to predict lung cancer risks to the general public. The model considers latent period, observation period, age dependency, and inherent risks from smoking or geographical location. A test of the model showed excellent agreement with results of the study of Czechoslovakian uranium miners, for which the necessary time factors were available. The risk model was also used to predict lung cancer incidence among residents of homes on reclaimed Florida phosphate lands, and results of this analysis indicate that over the space of many years, the increased incidence of lung cancer due to elevated radon levels may be indisgtinguishable from those due to other causes.
Risk assessment in diabetes management: how do general practitioners estimate risks due to diabetes?
Häussler, Bertram; Fischer, Gisela C; Meyer, Sibylle; Sturm, Diethard
2007-01-01
Objectives To evaluate the ability of general practitioners (GPs) in Germany to estimate the risk of patients with diabetes developing complications. Methods An interview study using a structured questionnaire to estimate risks of four case vignettes having diabetes‐specific complications within the next 10 years, risk reduction and life expectancy potential. A representative random sample of 584 GPs has been drawn, of which 150 could be interviewed. We compared GPs' estimates among each other (intraclass correlation coefficient (ICC) and Cohen's (multirater‐) κ) and with risks for long‐term complications generated by the multifactor disease model “Mellibase”, which is a knowledge‐based support system for medical decision management. Results The risk estimates by GPs varied widely (ICC 0.21 95% CI (0.13 to 0.36)). The average level of potential risk reduction was between 47% and 70%. Compared with Mellibase values, on average, the GPs overestimated the risk threefold. Mean estimates of potential prolongation of life expectancy were close to 10 years for each patient, whereas the Mellibase calculations ranged from 3 to 10 years. Conclusions Overestimation could lead to unnecessary care and waste of resources. PMID:17545348
Jonkman, Sebastiaan N; Jongejan, Ruben; Maaskant, Bob
2011-02-01
The Dutch government is in the process of revising its flood safety policy. The current safety standards for flood defenses in the Netherlands are largely based on the outcomes of cost-benefit analyses. Loss of life has not been considered separately in the choice for current standards. This article presents the results of a research project that evaluated the potential roles of two risk metrics, individual and societal risk, to support decision making about new flood safety standards. These risk metrics are already used in the Dutch major hazards policy for the evaluation of risks to the public. Individual risk concerns the annual probability of death of a person. Societal risk concerns the probability of an event with many fatalities. Technical aspects of the use of individual and societal risk metrics in flood risk assessments as well as policy implications are discussed. Preliminary estimates of nationwide levels of societal risk are presented. Societal risk levels appear relatively high in the southwestern part of the country where densely populated dike rings are threatened by a combination of river and coastal floods. It was found that cumulation, the simultaneous flooding of multiple dike rings during a single flood event, has significant impact on the national level of societal risk. Options for the application of the individual and societal risk in the new flood safety policy are presented and discussed.
Mazonakis, Michalis; Berris, Theoharris; Damilakis, John; Lyraraki, Efrossyni
2013-10-15
Purpose: Heterotopic ossification (HO) is a frequent complication following total hip arthroplasty. This study was conducted to calculate the radiation dose to organs-at-risk and estimate the probability of cancer induction from radiotherapy for HO prophylaxis.Methods: Hip irradiation for HO with a 6 MV photon beam was simulated with the aid of a Monte Carlo model. A realistic humanoid phantom representing an average adult patient was implemented in Monte Carlo environment for dosimetric calculations. The average out-of-field radiation dose to stomach, liver, lung, prostate, bladder, thyroid, breast, uterus, and ovary was calculated. The organ-equivalent-dose to colon, that was partly included within the treatment field, was also determined. Organ dose calculations were carried out using three different field sizes. The dependence of organ doses upon the block insertion into primary beam for shielding colon and prosthesis was investigated. The lifetime attributable risk for cancer development was estimated using organ, age, and gender-specific risk coefficients.Results: For a typical target dose of 7 Gy, organ doses varied from 1.0 to 741.1 mGy by the field dimensions and organ location relative to the field edge. Blocked field irradiations resulted in a dose range of 1.4–146.3 mGy. The most probable detriment from open field treatment of male patients was colon cancer with a high risk of 564.3 × 10{sup −5} to 837.4 × 10{sup −5} depending upon the organ dose magnitude and the patient's age. The corresponding colon cancer risk for female patients was (372.2–541.0) × 10{sup −5}. The probability of bladder cancer development was more than 113.7 × 10{sup −5} and 110.3 × 10{sup −5} for males and females, respectively. The cancer risk range to other individual organs was reduced to (0.003–68.5) × 10{sup −5}.Conclusions: The risk for cancer induction from radiation therapy for HO prophylaxis after total hip arthroplasty varies considerably by the
Cancer risks in BRCA2 families: estimates for sites other than breast and ovary
van Asperen, C J; Brohet, R; Meijers-Heijboer, E; Hoogerbrugge, N; Verhoef, S; Vasen, H; Ausems, M; Menko, F; Gomez, G; Klijn, J; Hogervorst, F; van Houwelingen, J C; van't, V; Rookus, M; van Leeuwen, F E; on, b
2005-01-01
Background: In BRCA2 mutation carriers, increased risks have been reported for several cancer sites besides breast and ovary. As most of the families included in earlier reports were selected on the basis of multiple breast/ovarian cancer cases, it is possible that risk estimates may differ in mutation carriers with a less striking family history. Methods: In the Netherlands, 139 BRCA2 families with 66 different pathogenic mutations were included in a nationwide study. To avoid testing bias, we chose not to estimate risk in typed carriers, but rather in male and female family members with a 50% prior probability of being a carrier (n = 1811). The relative risk (RR) for each cancer site with the exception of breast and ovarian cancer was determined by comparing observed numbers with those expected, based on Dutch cancer incidence rates. Results: We observed an excess risk for four cancer sites: pancreas (RR 5.9; 95% confidence interval (CI) 3.2 to 10.0), prostate (2.5; 1.6 to 3.8), bone (14.4; 2.9 to 42.1) and pharynx (7.3; 2.0 to 18.6). A small increase was observed for cancer of the digestive tract (1.5; 1.1 to 1.9). Histological verification was available for 46% of the tumours. Nearly all increased risks reached statistical significance for men only. Cancer risks tended to be higher for people before the age of 65 years. Moreover, families with mutations outside the previously defined ovarian cancer cluster region tended to have a higher cancer risk. Conclusions: We found that BRCA2 carriers are at increased risk for cancers of the prostate and pancreas, and possibly bone and pharynx. Larger databases with extended follow up are needed to provide insight into mutation specific risks of selected carriers in BRCA2 families. PMID:16141007
NASA Astrophysics Data System (ADS)
Veldkamp, T. I. E.; Wada, Y.; Aerts, J. C. J. H.; Ward, P. J.
2016-02-01
Changing hydro-climatic and socioeconomic conditions increasingly put pressure on fresh water resources and are expected to aggravate water scarcity conditions towards the future. Despite numerous calls for risk-based water scarcity assessments, a global-scale framework that includes UNISDR’s definition of risk does not yet exist. This study provides a first step towards such a risk-based assessment, applying a Gamma distribution to estimate water scarcity conditions at the global scale under historic and future conditions, using multiple climate change and population growth scenarios. Our study highlights that water scarcity risk, expressed in terms of expected annual exposed population, increases given all future scenarios, up to >56.2% of the global population in 2080. Looking at the drivers of risk, we find that population growth outweigh the impacts of climate change at global and regional scales. Using a risk-based method to assess water scarcity, we show the results to be less sensitive than traditional water scarcity assessments to the use of fixed threshold to represent different levels of water scarcity. This becomes especially important when moving from global to local scales, whereby deviations increase up to 50% of estimated risk levels.
NASA Technical Reports Server (NTRS)
Veldkamp, T. I. E.; Wada, Y.; Aerts, J. C. J. H.; Ward, P. J.
2016-01-01
Changing hydro-climatic and socioeconomic conditions increasingly put pressure on fresh water resources and are expected to aggravate water scarcity conditions towards the future. Despite numerous calls for risk-based water scarcity assessments, a global-scale framework that includes UNISDR's definition of risk does not yet exist. This study provides a first step towards such a risk based assessment, applying a Gamma distribution to estimate water scarcity conditions at the global scale under historic and future conditions, using multiple climate change and population growth scenarios. Our study highlights that water scarcity risk, expressed in terms of expected annual exposed population, increases given all future scenarios, up to greater than 56.2% of the global population in 2080. Looking at the drivers of risk, we find that population growth outweigh the impacts of climate change at global and regional scales. Using a risk-based method to assess water scarcity, we show the results to be less sensitive than traditional water scarcity assessments to the use of fixed threshold to represent different levels of water scarcity. This becomes especially important when moving from global to local scales, whereby deviations increase up to 50% of estimated risk levels.
Wagner, Daniel M.; Krieger, Joshua D.; Veilleux, Andrea G.
2016-08-04
In 2013, the U.S. Geological Survey initiated a study to update regional skew, annual exceedance probability discharges, and regional regression equations used to estimate annual exceedance probability discharges for ungaged locations on streams in the study area with the use of recent geospatial data, new analytical methods, and available annual peak-discharge data through the 2013 water year. An analysis of regional skew using Bayesian weighted least-squares/Bayesian generalized-least squares regression was performed for Arkansas, Louisiana, and parts of Missouri and Oklahoma. The newly developed constant regional skew of -0.17 was used in the computation of annual exceedance probability discharges for 281 streamgages used in the regional regression analysis. Based on analysis of covariance, four flood regions were identified for use in the generation of regional regression models. Thirty-nine basin characteristics were considered as potential explanatory variables, and ordinary least-squares regression techniques were used to determine the optimum combinations of basin characteristics for each of the four regions. Basin characteristics in candidate models were evaluated based on multicollinearity with other basin characteristics (variance inflation factor < 2.5) and statistical significance at the 95-percent confidence level (p ≤ 0.05). Generalized least-squares regression was used to develop the final regression models for each flood region. Average standard errors of prediction of the generalized least-squares models ranged from 32.76 to 59.53 percent, with the largest range in flood region D. Pseudo coefficients of determination of the generalized least-squares models ranged from 90.29 to 97.28 percent, with the largest range also in flood region D. The regional regression equations apply only to locations on streams in Arkansas where annual peak discharges are not substantially affected by regulation, diversion, channelization, backwater, or urbanization
Estimation of wildfire size and risk changes due to fuels treatments
Cochrane, M.A.; Moran, C.J.; Wimberly, M.C.; Baer, A.D.; Finney, M.A.; Beckendorf, K.L.; Eidenshink, J.; Zhu, Z.
2012-01-01
Human land use practices, altered climates, and shifting forest and fire management policies have increased the frequency of large wildfires several-fold. Mitigation of potential fire behaviour and fire severity have increasingly been attempted through pre-fire alteration of wildland fuels using mechanical treatments and prescribed fires. Despite annual treatment of more than a million hectares of land, quantitative assessments of the effectiveness of existing fuel treatments at reducing the size of actual wildfires or how they might alter the risk of burning across landscapes are currently lacking. Here, we present a method for estimating spatial probabilities of burning as a function of extant fuels treatments for any wildland fire-affected landscape. We examined the landscape effects of more than 72 000 ha of wildland fuel treatments involved in 14 large wildfires that burned 314 000 ha of forests in nine US states between 2002 and 2010. Fuels treatments altered the probability of fire occurrence both positively and negatively across landscapes, effectively redistributing fire risk by changing surface fire spread rates and reducing the likelihood of crowning behaviour. Trade offs are created between formation of large areas with low probabilities of increased burning and smaller, well-defined regions with reduced fire risk.
NASA Technical Reports Server (NTRS)
Holland, Frederic A., Jr.
2004-01-01
Modern engineering design practices are tending more toward the treatment of design parameters as random variables as opposed to fixed, or deterministic, values. The probabilistic design approach attempts to account for the uncertainty in design parameters by representing them as a distribution of values rather than as a single value. The motivations for this effort include preventing excessive overdesign as well as assessing and assuring reliability, both of which are important for aerospace applications. However, the determination of the probability distribution is a fundamental problem in reliability analysis. A random variable is often defined by the parameters of the theoretical distribution function that gives the best fit to experimental data. In many cases the distribution must be assumed from very limited information or data. Often the types of information that are available or reasonably estimated are the minimum, maximum, and most likely values of the design parameter. For these situations the beta distribution model is very convenient because the parameters that define the distribution can be easily determined from these three pieces of information. Widely used in the field of operations research, the beta model is very flexible and is also useful for estimating the mean and standard deviation of a random variable given only the aforementioned three values. However, an assumption is required to determine the four parameters of the beta distribution from only these three pieces of information (some of the more common distributions, like the normal, lognormal, gamma, and Weibull distributions, have two or three parameters). The conventional method assumes that the standard deviation is a certain fraction of the range. The beta parameters are then determined by solving a set of equations simultaneously. A new method developed in-house at the NASA Glenn Research Center assumes a value for one of the beta shape parameters based on an analogy with the normal
Krieger, D.J.; Hoehn, J.P.
1999-05-01
Obtaining economically consistent values for changes in low probability health risks continues to be a challenge for contingent valuation (CV) as well as for other valuation methods. One of the cited condition for economic consistency is that estimated values be sensitive to the scope (differences in quantity or quality) of a good described in a CV application. The alleged limitations of CV pose a particular problem for environmental managers who must often make decisions that affect human health risks. This paper demonstrates that a well-designed CV application can elicit scope sensitive values even for programs that provide conceptually complex goods such as risk reduction. Specifically, it finds that the amount sport anglers are willing to pay for information about chemical residues in fish varies systematically with informativeness--a relationship suggested by the theory of information value.
Attributable Risk Estimate of Severe Psoriasis on Major Cardiovascular Events
Mehta, Nehal N.; Yu, YiDing; Pinnelas, Rebecca; Krishnamoorthy, Parasuram; Shin, Daniel B.; Troxel, Andrea B.; Gelfand, Joel M.
2011-01-01
Background Recent studies suggest that psoriasis, particularly if severe, may be a risk factor for major adverse cardiac events such as myocardial infarction, stroke, and mortality from cardiovascular disease. We compared the risk of major adverse cardiac events between patients with psoriasis and the general population and estimated the attributable risk of severe psoriasis. Methods We performed a cohort study in the General Practice Research Database. Severe psoriasis was defined as receiving a psoriasis diagnosis and systemic therapy (N=3,603). Up to 4 patients without psoriasis were selected from the same practices and start dates for each patient with psoriasis (N=14,330). Results Severe psoriasis was a risk factor for major adverse cardiac events (hazard ratio 1.53; 95% confidence interval 1.26, 1.85) after adjusting for age, gender, diabetes, hypertension, tobacco use and hyperlipidemia. After fully adjusted analysis, severe psoriasis conferred an additional 6.2% absolute risk of 10-year major adverse cardiac events. Conclusions Severe psoriasis confers an additional 6.2% absolute risk of 10-year rate of major adverse cardiac events compared to the general population. This potentially has important therapeutic implications for cardiovascular risk stratification and prevention in patients with severe psoriasis. Future prospective studies are needed to validate these findings. PMID:21787906
Estimation of earthquake risk curves of physical building damage
NASA Astrophysics Data System (ADS)
Raschke, Mathias; Janouschkowetz, Silke; Fischer, Thomas; Simon, Christian
2014-05-01
In this study, a new approach to quantify seismic risks is presented. Here, the earthquake risk curves for the number of buildings with a defined physical damage state are estimated for South Africa. Therein, we define the physical damage states according to the current European macro-seismic intensity scale (EMS-98). The advantage of such kind of risk curve is that its plausibility can be checked more easily than for other types. The earthquake risk curve for physical building damage can be compared with historical damage and their corresponding empirical return periods. The number of damaged buildings from historical events is generally explored and documented in more detail than the corresponding monetary losses. The latter are also influenced by different economic conditions, such as inflation and price hikes. Further on, the monetary risk curve can be derived from the developed risk curve of physical building damage. The earthquake risk curve can also be used for the validation of underlying sub-models such as the hazard and vulnerability modules.
Estimating radiation risk induced by CT screening for Korean population
NASA Astrophysics Data System (ADS)
Yang, Won Seok; Yang, Hye Jeong; Min, Byung In
2017-02-01
The purposes of this study are to estimate the radiation risks induced by chest/abdomen computed tomography (CT) screening for healthcare and to determine the cancer risk level of the Korean population compared to other populations. We used an ImPACT CT Patient Dosimetry Calculator to compute the organ effective dose induced by CT screening (chest, low-dose chest, abdomen/pelvis, and chest/abdomen/pelvis CT). A risk model was applied using principles based on the BEIR VII Report in order to estimate the lifetime attributable risk (LAR) using the Korean Life Table 2010. In addition, several countries including Hong Kong, the United States (U.S.), and the United Kingdom, were selected for comparison. Herein, each population exposed radiation dose of 100 mSv was classified according to country, gender and age. For each CT screening the total organ effective dose calculated by ImPACT was 6.2, 1.5, 5.2 and 11.4 mSv, respectively. In the case of Korean female LAR, it was similar to Hong Kong female but lower than those of U.S. and U.K. females, except for those in their twenties. The LAR of Korean males was the highest for all types of CT screening. However, the difference of the risk level was negligible because of the quite low value.
NASA Technical Reports Server (NTRS)
Vitali, Roberto; Lutomski, Michael G.
2004-01-01
National Aeronautics and Space Administration s (NASA) International Space Station (ISS) Program uses Probabilistic Risk Assessment (PRA) as part of its Continuous Risk Management Process. It is used as a decision and management support tool to not only quantify risk for specific conditions, but more importantly comparing different operational and management options to determine the lowest risk option and provide rationale for management decisions. This paper presents the derivation of the probability distributions used to quantify the failure rates and the probability of failures of the basic events employed in the PRA model of the ISS. The paper will show how a Bayesian approach was used with different sources of data including the actual ISS on orbit failures to enhance the confidence in results of the PRA. As time progresses and more meaningful data is gathered from on orbit failures, an increasingly accurate failure rate probability distribution for the basic events of the ISS PRA model can be obtained. The ISS PRA has been developed by mapping the ISS critical systems such as propulsion, thermal control, or power generation into event sequences diagrams and fault trees. The lowest level of indenture of the fault trees was the orbital replacement units (ORU). The ORU level was chosen consistently with the level of statistically meaningful data that could be obtained from the aerospace industry and from the experts in the field. For example, data was gathered for the solenoid valves present in the propulsion system of the ISS. However valves themselves are composed of parts and the individual failure of these parts was not accounted for in the PRA model. In other words the failure of a spring within a valve was considered a failure of the valve itself.
At Risk of What? Possibilities over Probabilities in the Study of Young Lives
ERIC Educational Resources Information Center
Foster, Karen Rebecca; Spencer, Dale
2011-01-01
This paper draws on a series of 45 interviews with recipients of social assistance between the ages of 16 and 24 to offer a critical assessment of the language of "risk" and "resilience." After briefly tracing the development of this vocabulary and approach in youth research, this paper argues in line with existing critiques (Kelly 2000, te Riele…
Numeracy, Ratio Bias, and Denominator Neglect in Judgments of Risk and Probability
ERIC Educational Resources Information Center
Reyna, Valerie F.; Brainerd, Charles J.
2008-01-01
"Numeracy," so-called on analogy with literacy, is essential for making health and other social judgments in everyday life [Reyna, V. F., & Brainerd, C. J. (in press). The importance of mathematics in health and human judgment: Numeracy, risk communication, and medical decision making. "Learning and Individual Differences."]. Recent research on…
Fujimoto, Shinichiro; Kondo, Takeshi; Yamamoto, Hideya; Yokoyama, Naoyuki; Tarutani, Yasuhiro; Takamura, Kazuhisa; Urabe, Yoji; Konno, Kumiko; Nishizaki, Yuji; Shinozaki, Tomohiro; Kihara, Yasuki; Daida, Hiroyuki; Isshiki, Takaaki; Takase, Shinichi
2015-09-01
Existing methods to calculate pre-test probability of obstructive coronary artery disease (CAD) have been established using selected high-risk patients who were referred to conventional coronary angiography. The purpose of this study is to develop and validate our new method for pre-test probability of obstructive CAD using patients who underwent coronary CT angiography (CTA), which could be applicable to a wider range of patient population. Using consecutive 4137 patients with suspected CAD who underwent coronary CTA at our institution, a multivariate logistic regression model including clinical factors as covariates calculated the pre-test probability (K-score) of obstructive CAD determined by coronary CTA. The K-score was compared with the Duke clinical score using the area under the curve (AUC) for the receiver-operating characteristic curve. External validation was performed by an independent sample of 319 patients. The final model included eight significant predictors: age, gender, coronary risk factor (hypertension, diabetes mellitus, dyslipidemia, smoking), history of cerebral infarction, and chest symptom. The AUC of the K-score was significantly greater than that of the Duke clinical score for both derivation (0.736 vs. 0.699) and validation (0.714 vs. 0.688) data sets. Among patients who underwent coronary CTA, newly developed K-score had better pre-test prediction ability of obstructive CAD compared to Duke clinical score in Japanese population.
A Review of Expertise and Judgment Processes for Risk Estimation
R. L. Boring
2007-06-01
A major challenge of risk and reliability analysis for human errors or hardware failures is the need to enlist expert opinion in areas for which adequate operational data are not available. Experts enlisted in this capacity provide probabilistic estimates of reliability, typically comprised of a measure of central tendency and uncertainty bounds. While formal guidelines for expert elicitation are readily available, they largely fail to provide a theoretical basis for expertise and judgment. This paper reviews expertise and judgment in the context of risk analysis; overviews judgment biases, the role of training, and multivariate judgments; and provides guidance on the appropriate use of atomistic and holistic judgment processes.
Estimating Bird / Aircraft Collision Probabilities and Risk Utilizing Spatial Poisson Processes
2012-06-10
collisions of birds and objects in motion is wind turbine rotors. When a bird flies through the disc swept out by blades of a wind turbine rotor, the...Mathematical Model of Bird Collisions With Wind Turbine Rotors." Solar Energy Engineering 118 (1996): 253-262. 49 U.S. Air Force. "Air Force Instruction...Altitude Band] .............................................................. 44 viii List of Tables Table 1 USAF Wildlife Strikes by Phase of
Coe, J.A.; Godt, J.W.; Parise, M.; Moscariello, A.; ,
2003-01-01
We have used stratigraphic and historic records of debris-flows to estimate mean recurrence intervals of past debris-flow events on 19 fans along the Interstate 70 highway corridor in the Front Range of Colorado. Estimated mean recurrence intervals were used in the Poisson probability model to estimate the probability of future debris-flow events on the fans. Mean recurrence intervals range from 7 to about 2900 years. Annual probabilities range from less than 0.1% to about 13%. A regression analysis of mean recurrence interval data and drainage-basin morphometry yields a regression model that may be suitable to estimate mean recurrence intervals on fans with no stratigraphic or historic records. Additional work is needed to verify this model. ?? 2003 Millpress.
Jones, R; Kelly, L; French, N; England, T; Livesey, C; Wooldridge, M
2004-02-07
The risk of dispersing foot-and-mouth disease virus into the atmosphere, and spreading it to susceptible holdings as a result of burning large numbers of carcases together on open pyres, has been estimated for six selected pyres burned during the 2001 outbreak in the UK. The probability of an animal or holding becoming infected was dependent on the estimated level of exposure to the virus predicted from the concentrations of virus calculated by the Met Office, Bracknell. In general, the probability of infection per animal and per holding decreased as their distance from the pyre increased. In the case of two of the pyres, a holding under the pyre plumes became infected on a date consistent with when the pyre was lit. However, by calculating their estimated probability of infection from the pyres it was concluded that it was unlikely that in either case the pyre was the source of infection.
Buzeman, D G; Viano, D C; Lövsund, P
1998-09-01
Front occupant exposure, MAIS2+ and MAIS3+ injury risk, and maximum-injured body regions were studied in frontal offset impacts. The effect of overlap amount was evaluated in three data subsets from 9,902 accident-involved Volvo cars with at least SEK35,000 (= US$5,000) damage. The subsets were selected by a MAIS2+ or MAIS3+ injured co-occupant or by an equivalent barrier speed (EBS) > 20 mph, and consisted of 661 or 249 cases and 654 cases, respectively. Age and gender effects were minimized. Collisions with 1/3 to 2/3 overlap were most frequent, but the most injurious crash type was influenced by the data sorting technique. The EBS criterion seemed to select crashes of more comparable severity and this dataset may be most appropriate to evaluate overlap effects. With EBS > 20 mph, the highest injury risk occurred in 1/3 overlap crashes, at 62% for MAIS2+ and 44% for MAIS3+ injury. This was two to three times higher than the corresponding risk in full frontal crashes. Head and chest were the most severely injured body regions, but lower-extremity injuries became more important as overlap decreased.
NASA Astrophysics Data System (ADS)
Maghsoudi, Samira; Cesca, Simone; Hainzl, Sebastian; Kaiser, Diethelm; Becker, Dirk; Dahm, Torsten
2013-06-01
Reliable estimations of magnitude of completeness (Mc) are essential for a correct interpretation of seismic catalogues. The spatial distribution of Mc may be strongly variable and difficult to assess in mining environments, owing to the presence of galleries, cavities, fractured regions, porous media and different mineralogical bodies, as well as in consequence of inhomogeneous spatial distribution of the seismicity. We apply a 3-D modification of the probabilistic magnitude of completeness (PMC) method, which relies on the analysis of network detection capabilities. In our approach, the probability to detect an event depends on its magnitude, source-receiver Euclidian distance and source-receiver direction. The suggested method is proposed for study of the spatial distribution of the magnitude of completeness in a mining environment and here is applied to a 2-months acoustic emission (AE) data set recorded at the Morsleben salt mine, Germany. The dense seismic network and the large data set, which includes more than one million events, enable a detailed testing of the method. This method is proposed specifically for strongly heterogeneous media. Besides, it can also be used for specific network installations, with sensors with a sensitivity, dependent on the direction of the incoming wave (e.g. some piezoelectric sensors). In absence of strong heterogeneities, the standards PMC approach should be used. We show that the PMC estimations in mines strongly depend on the source-receiver direction, and cannot be correctly accounted using a standard PMC approach. However, results can be improved, when adopting the proposed 3-D modification of the PMC method. Our analysis of one central horizontal and vertical section yields a magnitude of completeness of about Mc ≈ 1 (AE magnitude) at the centre of the network, which increases up to Mc ≈ 4 at further distances outside the network; the best detection performance is estimated for a NNE-SSE elongated region, which
Improved risk estimates for carbon tetrachloride. 1998 annual progress report
Benson, J.M.; Springer, D.L.; Thrall, K.D.
1998-06-01
'The overall purpose of these studies is to improve the scientific basis for assessing the cancer risk associated with human exposure to carbon tetrachloride. Specifically, the toxicokinetics of inhaled carbon tetrachloride is being determined in rats, mice and hamsters. Species differences in the metabolism of carbon tetrachloride by rats, mice and hamsters is being determined in vivo and in vitro using tissues and microsomes from these rodent species and man. Dose-response relationships will be determined in all studies. The information will be used to improve the current physiologically based pharmacokinetic model for carbon tetrachloride. The authors will also determine whether carbon tetrachloride is a hepatocarcinogen only when exposure results in cell damage, cell killing, and regenerative cell proliferation. In combination, the results of these studies will provide the types of information needed to enable a refined risk estimate for carbon tetrachloride under EPA''s new guidelines for cancer risk assessment.'
Risk estimation based on chromosomal aberrations induced by radiation
NASA Technical Reports Server (NTRS)
Durante, M.; Bonassi, S.; George, K.; Cucinotta, F. A.
2001-01-01
The presence of a causal association between the frequency of chromosomal aberrations in peripheral blood lymphocytes and the risk of cancer has been substantiated recently by epidemiological studies. Cytogenetic analyses of crew members of the Mir Space Station have shown that a significant increase in the frequency of chromosomal aberrations can be detected after flight, and that such an increase is likely to be attributed to the radiation exposure. The risk of cancer can be estimated directly from the yields of chromosomal aberrations, taking into account some aspects of individual susceptibility and other factors unrelated to radiation. However, the use of an appropriate technique for the collection and analysis of chromosomes and the choice of the structural aberrations to be measured are crucial in providing sound results. Based on the fraction of aberrant lymphocytes detected before and after flight, the relative risk after a long-term Mir mission is estimated to be about 1.2-1.3. The new technique of mFISH can provide useful insights into the quantification of risk on an individual basis.
Estimation of tuberculosis risk on a commercial airliner.
Ko, Gwangpyo; Thompson, Kimberly M; Nardell, Edward A
2004-04-01
This article estimates the risk of tuberculosis (TB) transmission on a typical commercial airliner using a simple one box model (OBM) and a sequential box model (SBM). We used input data derived from an actual TB exposure on an airliner, and we assumed a hypothetical scenario that a highly infectious TB source case (i.e., 108 infectious quanta per hour) travels as a passenger on an 8.7-hour flight. We estimate an average risk of TB transmission on the order of 1 chance in 1,000 for all passengers using the OBM. Applying the more realistic SBM, we show that the risk and incidence decrease sharply in a stepwise fashion in cabins downstream from the cabin containing the source case assuming some potential for airflow from more contaminated to less contaminated cabins. We further characterized spatial variability in the risk within the cabin by modeling a previously reported TB outbreak in an airplane to demonstrate that the TB cases occur most likely within close proximity of the source TB patient.
Risk estimation of infectious diseases determines the effectiveness of the control strategy
NASA Astrophysics Data System (ADS)
Zhang, Haifeng; Zhang, Jie; Li, Ping; Small, Michael; Wang, Binghong
2011-05-01
Usually, whether to take vaccination or not is a voluntary decision, which is determined by many factors, from societal factors (such as religious belief and human rights) to individual preferences (including psychology and altruism). Facing the outbreaks of infectious diseases, different people often have different estimations on the risk of infectious diseases. So, some persons are willing to vaccinate, but other persons are willing to take risks. In this paper, we establish two different risk assessment systems using the technique of dynamic programming, and then compare the effects of the two different systems on the prevention of diseases on complex networks. One is that the perceived probability of being infected for each individual is the same (uniform case). The other is that the perceived probability of being infected is positively correlated to individual degrees (preferential case). We show that these two risk assessment systems can yield completely different results, such as, the effectiveness of controlling diseases, the time evolution of the number of infections, and so on.
Markiewicz, Łukasz; Kubińska, Elżbieta
2015-01-01
Objective: This paper aims to provide insight into information processing differences between hot and cold risk taking decision tasks within a single domain. Decision theory defines risky situations using at least three parameters: outcome one (often a gain) with its probability and outcome two (often a loss) with a complementary probability. Although a rational agent should consider all of the parameters, s/he could potentially narrow their focus to only some of them, particularly when explicit Type 2 processes do not have the resources to override implicit Type 1 processes. Here we investigate differences in risky situation parameters' influence on hot and cold decisions. Although previous studies show lower information use in hot than in cold processes, they do not provide decision weight changes and therefore do not explain whether this difference results from worse concentration on each parameter of a risky situation (probability, gain amount, and loss amount) or from ignoring some parameters. Methods: Two studies were conducted, with participants performing the Columbia Card Task (CCT) in either its Cold or Hot version. In the first study, participants also performed the Cognitive Reflection Test (CRT) to monitor their ability to override Type 1 processing cues (implicit processes) with Type 2 explicit processes. Because hypothesis testing required comparison of the relative importance of risky situation decision weights (gain, loss, probability), we developed a novel way of measuring information use in the CCT by employing a conjoint analysis methodology. Results: Across the two studies, results indicated that in the CCT Cold condition decision makers concentrate on each information type (gain, loss, probability), but in the CCT Hot condition they concentrate mostly on a single parameter: probability of gain/loss. We also show that an individual's CRT score correlates with information use propensity in cold but not hot tasks. Thus, the affective dimension of
Britton, Annie; O’Neill, Darragh; Bell, Steven
2016-01-01
Aims Increases in glass sizes and wine strength over the last 25 years in the UK are likely to have led to an underestimation of alcohol intake in population studies. We explore whether this probable misclassification affects the association between average alcohol intake and risk of mortality from all causes, cardiovascular disease and cancer. Methods Self-reported alcohol consumption in 1997–1999 among 7010 men and women in the Whitehall II cohort of British civil servants was linked to the risk of mortality until mid-2015. A conversion factor of 8 g of alcohol per wine glass (1 unit) was compared with a conversion of 16 g per wine glass (2 units). Results When applying a higher alcohol content conversion for wine consumption, the proportion of heavy/very heavy drinkers increased from 28% to 41% for men and 15% to 28% for women. There was a significantly increased risk of very heavy drinking compared with moderate drinking for deaths from all causes and cancer before and after change in wine conversion; however, the hazard ratios were reduced when a higher wine conversion was used. Conclusions In this population-based study, assuming higher alcohol content in wine glasses changed the estimates of mortality risk. We propose that investigator-led cohorts need to revisit conversion factors based on more accurate estimates of alcohol content in wine glasses. Prospectively, researchers need to collect more detailed information on alcohol including serving sizes and strength. Short summary The alcohol content in a wine glass is likely to be underestimated in population surveys as wine strength and serving size have increased in recent years. We demonstrate that in a large cohort study, this underestimation affects estimates of mortality risk. Investigator-led cohorts need to revisit conversion factors based on more accurate estimates of alcohol content in wine glasses. PMID:27261472
Gennai, S; Rallo, A; Keil, D; Seigneurin, A; Germi, R; Epaulard, O
2016-06-01
Herpes simplex virus (HSV) encephalitis is associated with a high risk of mortality and sequelae, and early diagnosis and treatment in the emergency department are necessary. However, most patients present with non-specific febrile, acute neurologic impairment; this may lead clinicians to overlook the diagnosis of HSV encephalitis. We aimed to identify which data collected in the first hours in a medical setting were associated with the diagnosis of HSV encephalitis. We conducted a multicenter retrospective case-control study in four French public hospitals from 2007 to 2013. The cases were the adult patients who received a confirmed diagnosis of HSV encephalitis. The controls were all the patients who attended the emergency department of Grenoble hospital with a febrile acute neurologic impairment, without HSV detection by polymerase chain reaction (PCR) in the cerebrospinal fluid (CSF), in 2012 and 2013. A multivariable logistic model was elaborated to estimate factors significantly associated with HSV encephalitis. Finally, an HSV probability score was derived from the logistic model. We identified 36 cases and 103 controls. Factors independently associated with HSV encephalitis were the absence of past neurological history (odds ratio [OR] 6.25 [95 % confidence interval (CI): 2.22-16.7]), the occurrence of seizure (OR 8.09 [95 % CI: 2.73-23.94]), a systolic blood pressure ≥140 mmHg (OR 5.11 [95 % CI: 1.77-14.77]), and a C-reactive protein <10 mg/L (OR 9.27 [95 % CI: 2.98-28.88]). An HSV probability score was calculated summing the value attributed to each independent factor. HSV encephalitis diagnosis may benefit from the use of this score based upon some easily accessible data. However, diagnostic evocation and probabilistic treatment must remain the rule.
Risk cross sections and their application to risk estimation in the galactic cosmic-ray environment
NASA Technical Reports Server (NTRS)
Curtis, S. B.; Nealy, J. E.; Wilson, J. W.; Chatterjee, A. (Principal Investigator)
1995-01-01
Radiation risk cross sections (i.e. risks per particle fluence) are discussed in the context of estimating the risk of radiation-induced cancer on long-term space flights from the galactic cosmic radiation outside the confines of the earth's magnetic field. Such quantities are useful for handling effects not seen after low-LET radiation. Since appropriate cross-section functions for cancer induction for each particle species are not yet available, the conventional quality factor is used as an approximation to obtain numerical results for risks of excess cancer mortality. Risks are obtained for seven of the most radiosensitive organs as determined by the ICRP [stomach, colon, lung, bone marrow (BFO), bladder, esophagus and breast], beneath 10 g/cm2 aluminum shielding at solar minimum. Spectra are obtained for excess relative risk for each cancer per LET interval by calculating the average fluence-LET spectrum for the organ and converting to risk by multiplying by a factor proportional to R gamma L Q(L) before integrating over L, the unrestricted LET. Here R gamma is the risk coefficient for low-LET radiation (excess relative mortality per Sv) for the particular organ in question. The total risks of excess cancer mortality obtained are 1.3 and 1.1% to female and male crew, respectively, for a 1-year exposure at solar minimum. Uncertainties in these values are estimated to range between factors of 4 and 15 and are dominated by the biological uncertainties in the risk coefficients for low-LET radiation and in the LET (or energy) dependence of the risk cross sections (as approximated by the quality factor). The direct substitution of appropriate risk cross sections will eventually circumvent entirely the need to calculate, measure or use absorbed dose, equivalent dose and quality factor for such a high-energy charged-particle environment.
Leukemia risk associated with benzene exposure in the pliofilm cohort. II. Risk estimates.
Paxton, M B; Chinchilli, V M; Brett, S M; Rodricks, J V
1994-04-01
The detailed work histories of the individual workers composing the Pliofilm cohort represent a unique resource for estimating the dose-response for leukemia that may follow occupational exposure to benzene. In this paper, we report the results of analyzing the updated Pliofilm cohort using the proportional hazards model, a more sophisticated technique that uses more of the available exposure data than the conditional logistic model used by Rinsky et al. The more rigorously defined exposure estimates derived by Paustenbach et al. are consistent with those of Crump and Allen in giving estimates of the slope of the leukemogenic dose-response that are not as steep as the slope resulting from the exposure estimates of Rinsky et al. We consider estimates of 0.3-0.5 additional leukemia deaths per thousand workers with 45 ppm-years of cumulative benzene exposure to be the best estimates currently available of leukemia risk from occupational exposure to benzene. These risks were estimated in the proportional hazards model when the exposure estimates of Crump and Allen or of Paustenbach et al. were used to derive a cumulative concentration-by-time metric.
Usuda, Kan; Ueno, Takaaki; Ito, Yuichi; Dote, Tomotaro; Yokoyama, Hirotaka; Kono, Koichi; Tamaki, Junko
2016-09-01
The present risk assessment study of fluoride salts was conducted by oral administration of three different doses of sodium and potassium fluorides (NaF, KF) and zinc fluoride tetrahydrate (ZnF2 •4H2O) to male Wistar rats. The rats were divided into control and nine experimental groups, to which oral injections of 0.5 mL distilled water and 0.5 mL of fluoride solutions, respectively, were given. The dosage of fluoride compounds was adjusted to contain 2.1 mg (low-dose group, LG), 4.3 mg (mid-dose group, MG), and 5.4 mg fluoride per 200 g rat body weight (high-dose group, HG) corresponding to 5, 10, and 12.5 % of LD50 values for NaF. The 24-h urine volume, N-acetyl-β-D-glucosaminidase (NAG) and creatinine clearance (Ccr) were measured as markers of possible acute renal impact. The levels of alanine aminotransferase (ALT) and aspartate aminotransferase (AST) were determined in serum samples as markers of acute hepatic impact. The levels of serum and urinary fluoride were determined to evaluate fluoride bioavailability. The results reveal that higher doses of NaF, KF, and ZnF2 induced renal damage as indicated by higher urinary NAG (p < 0.05 with ≥90th percentile of control). High doses of ZnF2 also induced a significant Ccr decrease (p < 0.05 with ≤10th percentile of control). Low doses of NaF and mid-doses of ZnF2 induced polyuria (p < 0.05 with ≥90th percentile of control) while medium doses of NaF and low doses of KF also induced liver damage, as indicated by a high level of AST (p < 0.05 with ≥90th percentile of control). These findings suggest that oral administration of fluoride is a potential, dose-dependent risk factor of renal tubular damage.
NASA Technical Reports Server (NTRS)
George, Kerry A.; Rhone, J.; Chappell, L. J.; Cucinotta, F. A.
2011-01-01
To date, cytogenetic damage has been assessed in blood lymphocytes from more than 30 astronauts before and after they participated in long-duration space missions of three months or more on board the International Space Station. Chromosome damage was assessed using fluorescence in situ hybridization whole chromosome analysis techniques. For all individuals, the frequency of chromosome damage measured within a month of return from space was higher than their preflight yield, and biodosimetry estimates were within the range expected from physical dosimetry. Follow up analyses have been performed on most of the astronauts at intervals ranging from around 6 months to many years after flight, and the cytogenetic effects of repeat long-duration missions have so far been assessed in four individuals. Chromosomal aberrations in peripheral blood lymphocytes have been validated as biomarkers of cancer risk and cytogenetic damage can therefore be used to characterize excess health risk incurred by individual crewmembers after their respective missions. Traditional risk assessment models are based on epidemiological data obtained on Earth in cohorts exposed predominantly to acute doses of gamma-rays, and the extrapolation to the space environment is highly problematic, involving very large uncertainties. Cytogenetic damage could play a key role in reducing uncertainty in risk estimation because it is incurred directly in the space environment, using specimens from the astronauts themselves. Relative cancer risks were estimated from the biodosimetry data using the quantitative approach derived from the European Study Group on Cytogenetic Biomarkers and Health database. Astronauts were categorized into low, medium, or high tertiles according to their yield of chromosome damage. Age adjusted tertile rankings were used to estimate cancer risk and results were compared with values obtained using traditional modeling approaches. Individual tertile rankings increased after space
The model-based estimates of important cancer risk factors and screening behaviors are obtained by combining the responses to the Behavioral Risk Factor Surveillance System (BRFSS) and the National Health Interview Survey (NHIS).
Spatio-temporal population estimates for risk management
NASA Astrophysics Data System (ADS)
Cockings, Samantha; Martin, David; Smith, Alan; Martin, Rebecca
2013-04-01
Accurate estimation of population at risk from hazards and effective emergency management of events require not just appropriate spatio-temporal modelling of hazards but also of population. While much recent effort has been focused on improving the modelling and predictions of hazards (both natural and anthropogenic), there has been little parallel advance in the measurement or modelling of population statistics. Different hazard types occur over diverse temporal cycles, are of varying duration and differ significantly in their spatial extent. Even events of the same hazard type, such as flood events, vary markedly in their spatial and temporal characteristics. Conceptually and pragmatically then, population estimates should also be available for similarly varying spatio-temporal scales. Routine population statistics derived from traditional censuses or surveys are usually static representations in both space and time, recording people at their place of usual residence on census/survey night and presenting data for administratively defined areas. Such representations effectively fix the scale of population estimates in both space and time, which is unhelpful for meaningful risk management. Over recent years, the Pop24/7 programme of research, based at the University of Southampton (UK), has developed a framework for spatio-temporal modelling of population, based on gridded population surfaces. Based on a data model which is fully flexible in terms of space and time, the framework allows population estimates to be produced for any time slice relevant to the data contained in the model. It is based around a set of origin and destination centroids, which have capacities, spatial extents and catchment areas, all of which can vary temporally, such as by time of day, day of week, season. A background layer, containing information on features such as transport networks and landuse, provides information on the likelihood of people being in certain places at specific times
Austin, Peter C
2010-09-10
Propensity score methods are increasingly being used to estimate the effects of treatments on health outcomes using observational data. There are four methods for using the propensity score to estimate treatment effects: covariate adjustment using the propensity score, stratification on the propensity score, propensity-score matching, and inverse probability of treatment weighting (IPTW) using the propensity score. When outcomes are binary, the effect of treatment on the outcome can be described using odds ratios, relative risks, risk differences, or the number needed to treat. Several clinical commentators suggested that risk differences and numbers needed to treat are more meaningful for clinical decision making than are odds ratios or relative risks. However, there is a paucity of information about the relative performance of the different propensity-score methods for estimating risk differences. We conducted a series of Monte Carlo simulations to examine this issue. We examined bias, variance estimation, coverage of confidence intervals, mean-squared error (MSE), and type I error rates. A doubly robust version of IPTW had superior performance compared with the other propensity-score methods. It resulted in unbiased estimation of risk differences, treatment effects with the lowest standard errors, confidence intervals with the correct coverage rates, and correct type I error rates. Stratification, matching on the propensity score, and covariate adjustment using the propensity score resulted in minor to modest bias in estimating risk differences. Estimators based on IPTW had lower MSE compared with other propensity-score methods. Differences between IPTW and propensity-score matching may reflect that these two methods estimate the average treatment effect and the average treatment effect for the treated, respectively.
Mao, Lu; Lin, D Y
2017-03-01
The cumulative incidence is the probability of failure from the cause of interest over a certain time period in the presence of other risks. A semiparametric regression model proposed by Fine and Gray (1999) has become the method of choice for formulating the effects of covariates on the cumulative incidence. Its estimation, however, requires modeling of the censoring distribution and is not statistically efficient. In this paper, we present a broad class of semiparametric transformation models which extends the Fine and Gray model, and we allow for unknown causes of failure. We derive the nonparametric maximum likelihood estimators (NPMLEs) and develop simple and fast numerical algorithms using the profile likelihood. We establish the consistency, asymptotic normality, and semiparametric efficiency of the NPMLEs. In addition, we construct graphical and numerical procedures to evaluate and select models. Finally, we demonstrate the advantages of the proposed methods over the existing ones through extensive simulation studies and an application to a major study on bone marrow transplantation.
Estimating Worker Risk Levels Using Accident/Incident Data
Kenoyer, Judson L.; Stenner, Robert D.; Andrews, William B.; Scherpelz, Robert I.; Aaberg, Rosanne L.
2000-09-26
The purpose of the work described in this report was to identify methods that are currently being used in the Department of Energy (DOE) complex to identify and control hazards/risks in the workplace, evaluate them in terms of their effectiveness in reducing risk to the workers, and to develop a preliminary method that could be used to predict the relative risks to workers performing proposed tasks using some of the current methodology. This report describes some of the performance indicators (i.e., safety metrics) that are currently being used to track relative levels of workplace safety in the DOE complex, how these fit into an Integrated Safety Management (ISM) system, some strengths and weaknesses of using a statistically based set of indicators, and methods to evaluate them. Also discussed are methods used to reduce risk to the workers and some of the techniques that appear to be working in the process of establishing a condition of continuous improvement. The results of these methods will be used in future work involved with the determination of modifying factors for a more complex model. The preliminary method to predict the relative risk level to workers during an extended future time period is based on a currently used performance indicator that uses several factors tracked in the CAIRS. The relative risks for workers in a sample (but real) facility on the Hanford site are estimated for a time period of twenty years and are based on workforce predictions. This is the first step in developing a more complex model that will incorporate other modifying factors related to the workers, work environment and status of the ISM system to adjust the preliminary prediction.
Ennis, Erin J; Foley, Joe P
2016-07-15
A stochastic approach was utilized to estimate the probability of a successful isocratic or gradient separation in conventional chromatography for numbers of sample components, peak capacities, and saturation factors ranging from 2 to 30, 20-300, and 0.017-1, respectively. The stochastic probabilities were obtained under conditions of (i) constant peak width ("gradient" conditions) and (ii) peak width increasing linearly with time ("isocratic/constant N" conditions). The isocratic and gradient probabilities obtained stochastically were compared with the probabilities predicted by Martin et al. [Anal. Chem., 58 (1986) 2200-2207] and Davis and Stoll [J. Chromatogr. A, (2014) 128-142]; for a given number of components and peak capacity the same trend is always observed: probability obtained with the isocratic stochastic approach<probability obtained with the gradient stochastic approach≤probability predicted by Davis and Stoll < probability predicted by Martin et al. The differences are explained by the positive bias of the Martin equation and the lower average resolution observed for the isocratic simulations compared to the gradient simulations with the same peak capacity. When the stochastic results are applied to conventional HPLC and sequential elution liquid chromatography (SE-LC), the latter is shown to provide much greater probabilities of success for moderately complex samples (e.g., PHPLC=31.2% versus PSE-LC=69.1% for 12 components and the same analysis time). For a given number of components, the density of probability data provided over the range of peak capacities is sufficient to allow accurate interpolation of probabilities for peak capacities not reported, <1.5% error for saturation factors <0.20. Additional applications for the stochastic approach include isothermal and programmed-temperature gas chromatography.
Global Building Inventory for Earthquake Loss Estimation and Risk Management
Jaiswal, Kishor; Wald, David; Porter, Keith
2010-01-01
We develop a global database of building inventories using taxonomy of global building types for use in near-real-time post-earthquake loss estimation and pre-earthquake risk analysis, for the U.S. Geological Survey’s Prompt Assessment of Global Earthquakes for Response (PAGER) program. The database is available for public use, subject to peer review, scrutiny, and open enhancement. On a country-by-country level, it contains estimates of the distribution of building types categorized by material, lateral force resisting system, and occupancy type (residential or nonresidential, urban or rural). The database draws on and harmonizes numerous sources: (1) UN statistics, (2) UN Habitat’s demographic and health survey (DHS) database, (3) national housing censuses, (4) the World Housing Encyclopedia and (5) other literature.
A probabilistic method for the estimation of residual risk in donated blood.
Bish, Ebru K; Ragavan, Prasanna K; Bish, Douglas R; Slonim, Anthony D; Stramer, Susan L
2014-10-01
The residual risk (RR) of transfusion-transmitted infections, including the human immunodeficiency virus and hepatitis B and C viruses, is typically estimated by the incidence[Formula: see text]window period model, which relies on the following restrictive assumptions: Each screening test, with probability 1, (1) detects an infected unit outside of the test's window period; (2) fails to detect an infected unit within the window period; and (3) correctly identifies an infection-free unit. These assumptions need not hold in practice due to random or systemic errors and individual variations in the window period. We develop a probability model that accurately estimates the RR by relaxing these assumptions, and quantify their impact using a published cost-effectiveness study and also within an optimization model. These assumptions lead to inaccurate estimates in cost-effectiveness studies and to sub-optimal solutions in the optimization model. The testing solution generated by the optimization model translates into fewer expected infections without an increase in the testing cost.
1988-09-01
Finite state space semi-Markov process find application in many areas. Often interest centers on whether or not the process has hit a particular state before a time t. This thesis reports results of a simulation study of the small behavior for three estimators of the survival probability of a first passage time for a semi-Markov process using censored data. Keywords: Semi- Markov; Kaplan Meier estimator; Confidence interval ; Jackknife; Problem; Theses.
Betancourt, Walter Q; Duarte, Diana C; Vásquez, Rosa C; Gurian, Patrick L
2014-08-15
Sewage is a major contributor to pollution problems involving human pathogens in tropical coastal areas. This study investigated the occurrence of intestinal protozoan parasites (Giardia and Cryptosporidium) in tropical recreational marine waters contaminated with sewage. The potential risks of Cryptosporidium and Giardia infection from recreational water exposure were estimated from the levels of viable (oo) cysts (DIC+, DAPI+, PI-) found in near-shore swimming areas using an exponential dose response model. A Monte Carlo uncertainty analysis was performed in order to determine the probability distribution of risks. Microbial indicators of recreational water quality (enterococci, Clostridium perfringens) and genetic markers of sewage pollution (human-specific Bacteroidales marker [HF183] and Clostridium coccoides) were simultaneously evaluated in order to estimate the extent of water quality deterioration associated with human wastes. The study revealed the potential risk of parasite infections via primary contact with tropical marine waters contaminated with sewage; higher risk estimates for Giardia than for Cryptosporidium were found. Mean risks estimated by Monte Carlo were below the U.S. EPA upper bound on recreational risk of 0.036 for cryptosporidiosis and giardiasis for both children and adults. However, 95th percentile estimates for giardiasis for children exceeded the 0.036 level. Environmental surveillance of microbial pathogens is crucial in order to control and eradicate the effects that increasing anthropogenic impacts have on marine ecosystems and human health.
NASA Technical Reports Server (NTRS)
Huddleston, Lisa L.; Roeder, William; Merceret, Francis J.
2010-01-01
A technique has been developed to calculate the probability that any nearby lightning stroke is within any radius of any point of interest. In practice, this provides the probability that a nearby lightning stroke was within a key distance of a facility, rather than the error ellipses centered on the stroke. This process takes the current bivariate Gaussian distribution of probability density provided by the current lightning location error ellipse for the most likely location of a lightning stroke and integrates it to get the probability that the stroke is inside any specified radius. This new facility-centric technique will be much more useful to the space launch customers and may supersede the lightning error ellipse approach discussed in [5], [6].
Rabiul Islam, G M; Habib, Mohammad Ruzlan; Waid, Jillian L; Rahman, M Safiur; Kabir, J; Akter, S; Jolly, Y N
2017-03-01
An assessment of the dietary risk of heavy metal exposure to humans is important since it is the main source of exposure. This study aimed to estimate the degree of contamination and assess the probable health risk in the prawn food chain. In prawn feed, the concentrations of metals were detected in the following order: Hg > Co > Pb > Cd. The concentrations of heavy metals in prawn were the highest for Co and lowest for Cd. Trace amounts of As and Cr were detected in the analyzed sample. Target hazard quotients for heavy metals for adults were >1 for Pb, Cd, Hg, and Co, and for children, the same were high for Co and Hg, indicating significant health risks upon dietary exposure. All the prawn samples contained nine-fold and fourteen-fold higher concentrations than the maximum acceptable levels for Pb and Hg, respectively (0.5 mg kg(-1); WHO/FAO). Human health risk due to the Co exposure is quite alarming as the level of exposure was found to be very high. In the prawn samples intended for human consumption, the hazard index (HI) was highest in the samples obtained from Bagerhat (3.25 in flesh and 3.26 in skin), followed by the samples obtained from Satkhira (2.84 in flesh and 3.10 in skin) and Dhaka City Corporation (2.81 in flesh and 3.42 in Skin); this indicates a potential risk of prawn consumption obtained from Southeast Bangladesh. This is particularly problematic as this area accounts for the majority of prawn production and export of the country.
NASA Technical Reports Server (NTRS)
Cross, Robert
2005-01-01
Until Solid Rocket Motor ignition, the Space Shuttle is mated to the Mobil Launch Platform in part via eight (8) Solid Rocket Booster (SRB) hold-down bolts. The bolts are fractured using redundant pyrotechnics, and are designed to drop through a hold-down post on the Mobile Launch Platform before the Space Shuttle begins movement. The Space Shuttle program has experienced numerous failures where a bolt has "hung-up." That is, it did not clear the hold-down post before liftoff and was caught by the SRBs. This places an additional structural load on the vehicle that was not included in the original certification requirements. The Space Shuttle is currently being certified to withstand the loads induced by up to three (3) of eight (8) SRB hold-down post studs experiencing a "hang-up." The results af loads analyses performed for four (4) stud-hang ups indicate that the internal vehicle loads exceed current structural certification limits at several locations. To determine the risk to the vehicle from four (4) stud hang-ups, the likelihood of the scenario occurring must first be evaluated. Prior to the analysis discussed in this paper, the likelihood of occurrence had been estimated assuming that the stud hang-ups were completely independent events. That is, it was assumed that no common causes or factors existed between the individual stud hang-up events. A review of the data associated with the hang-up events, showed that a common factor (timing skew) was present. This paper summarizes a revised likelihood evaluation performed for the four (4) stud hang-ups case considering that there are common factors associated with the stud hang-ups. The results show that explicitly (i.e. not using standard common cause methodologies such as beta factor or Multiple Greek Letter modeling) taking into account the common factor of timing skew results in an increase in the estimated likelihood of four (4) stud hang-ups of an order of magnitude over the independent failure case.
NASA Technical Reports Server (NTRS)
Cross, Robert
2005-01-01
Until Solid Rocket Motor ignition, the Space Shuttle is mated to the Mobil Launch Platform in part via eight (8) Solid Rocket Booster (SRB) hold-down bolts. The bolts are fractured using redundant pyrotechnics, and are designed to drop through a hold-down post on the Mobile Launch Platform before the Space Shuttle begins movement. The Space Shuttle program has experienced numerous failures where a bolt has hung up. That is, it did not clear the hold-down post before liftoff and was caught by the SRBs. This places an additional structural load on the vehicle that was not included in the original certification requirements. The Space Shuttle is currently being certified to withstand the loads induced by up to three (3) of eight (8) SRB hold-down experiencing a "hang-up". The results of loads analyses performed for (4) stud hang-ups indicate that the internal vehicle loads exceed current structural certification limits at several locations. To determine the risk to the vehicle from four (4) stud hang-ups, the likelihood of the scenario occurring must first be evaluated. Prior to the analysis discussed in this paper, the likelihood of occurrence had been estimated assuming that the stud hang-ups were completely independent events. That is, it was assumed that no common causes or factors existed between the individual stud hang-up events. A review of the data associated with the hang-up events, showed that a common factor (timing skew) was present. This paper summarizes a revised likelihood evaluation performed for the four (4) stud hang-ups case considering that there are common factors associated with the stud hang-ups. The results show that explicitly (i.e. not using standard common cause methodologies such as beta factor or Multiple Greek Letter modeling) taking into account the common factor of timing skew results in an increase in the estimated likelihood of four (4) stud hang-ups of an order of magnitude over the independent failure case.
Austin, Peter C; Stuart, Elizabeth A
2015-12-10
The propensity score is defined as a subject's probability of treatment selection, conditional on observed baseline covariates. Weighting subjects by the inverse probability of treatment received creates a synthetic sample in which treatment assignment is independent of measured baseline covariates. Inverse probability of treatment weighting (IPTW) using the propensity score allows one to obtain unbiased estimates of average treatment effects. However, these estimates are only valid if there are no residual systematic differences in observed baseline characteristics between treated and control subjects in the sample weighted by the estimated inverse probability of treatment. We report on a systematic literature review, in which we found that the use of IPTW has increased rapidly in recent years, but that in the most recent year, a majority of studies did not formally examine whether weighting balanced measured covariates between treatment groups. We then proceed to describe a suite of quantitative and qualitative methods that allow one to assess whether measured baseline covariates are balanced between treatment groups in the weighted sample. The quantitative methods use the weighted standardized difference to compare means, prevalences, higher-order moments, and interactions. The qualitative methods employ graphical methods to compare the distribution of continuous baseline covariates between treated and control subjects in the weighted sample. Finally, we illustrate the application of these methods in an empirical case study. We propose a formal set of balance diagnostics that contribute towards an evolving concept of 'best practice' when using IPTW to estimate causal treatment effects using observational data.
ERIC Educational Resources Information Center
Herek, Gregory M.
2009-01-01
Using survey responses collected via the Internet from a U.S. national probability sample of gay, lesbian, and bisexual adults (N = 662), this article reports prevalence estimates of criminal victimization and related experiences based on the target's sexual orientation. Approximately 20% of respondents reported having experienced a person or…
NASA Astrophysics Data System (ADS)
Kanae, S.; Seto, S.; Yoshimura, K.; Oki, T.
2008-12-01
A new river discharge prediction and hindcast system all over Japan in order to issue alerts of flood risks has been developed. It utilizes Japan Meteorological Agency"fs Meso-scale model outputs and remote-sensing precipitation data. A statistical approach that compromises the bias and uncertainty of models is proposed for interpreting the simulated river discharge as a flood risk. A 29-year simulation was implemented to estimate parameters of the Gumbel distribution for the probability of extreme discharge, and the estimated discharge probability index (DPI) showed good agreement with that estimated based on observations. Even more strikingly, high DPI in the simulation corresponded to actual flood damage records. This indicates that the real-time simulation of the DPI could potentially provide reasonable flood warnings. A method to overcome the lack of sufficiently long simulation data through the use of a pre-existing long-term simulation and to estimate statistical parameters is also proposed. A preliminary flood risk prediction that used operational weather forecast data for 2003 and 2004 gave results similar to those of the 29-year simulation for the Typhoon T0423 event on October 2004, demonstrating the transferability of the technique to real-time prediction. In addition, the usefulness of satellite precipitation data for the flood estimation is evaluated via hindcast. We conducted it using several precipitation satellite datasets. The GSMaP product can detect heavy precipitation events, but floods being not well simulated in many cases because of GSMAP"fs underestimation. The GSMaP product adjusted by using monthly and 1 degree rain gauge information can be used to detect flood events as well as hourly rain gauge observations. Another quantitative issue is also disscussed. When a remote-sensing based precipitation data is used as an input for hindcast, we are suffering from underestimation of precipitation amount. The effort for improvement will be shown
Estimate of the risks of disposing nonhazardous oil field wastes into salt caverns
Tomasko, D.; Elcock, D.; Veil, J.
1997-12-31
Argonne National Laboratory (ANL) has completed an evaluation of the possibility that adverse human health effects (carcinogenic and noncarcinogenic) could result from exposure to contaminants released from nonhazardous oil field wastes (NOW) disposed in domal salt caverns. Potential human health risks associated with hazardous substances (arsenic, benzene, cadmium, and chromium) in NOW were assessed under four postclosure cavern release scenarios: inadvertent cavern intrusion, failure of the cavern seal, failure of the cavern through cracks or leaky interbeds, and a partial collapse of the cavern roof. To estimate potential human health risks for these scenarios, contaminant concentrations at the receptor were calculated using a one-dimensional solution to an advection/dispersion equation that included first order degradation. Assuming a single, generic salt cavern and generic oil-field wastes, the best-estimate excess cancer risks ranged from 1.7 {times} 10{sup {minus}12} to 1.1 {times} 10{sup {minus}8} and hazard indices (referring to noncancer health effects) ranged from 7 {times} 10{sup {minus}9} to 7 {times} 10{sup {minus}4}. Under worse-case conditions in which the probability of cavern failure is 1.0, excess cancer risks ranged from 4.9 {times} 10{sup {minus}9} to 1.7 {times} 10{sup {minus}5} and hazard indices ranged from 7.0 {times} 10{sup {minus}4} to 0.07. Even under worst-case conditions, the risks are within the US Environmental Protection Agency (EPA) target range for acceptable exposure levels. From a human health risk perspective, salt caverns can, therefore, provide an acceptable disposal method for NOW.
Potential Biases in Estimating Absolute and Relative Case-Fatality Risks during Outbreaks
Lipsitch, Marc; Donnelly, Christl A.; Fraser, Christophe; Blake, Isobel M.; Cori, Anne; Dorigatti, Ilaria; Ferguson, Neil M.; Garske, Tini; Mills, Harriet L.; Riley, Steven; Van Kerkhove, Maria D.; Hernán, Miguel A.
2015-01-01
Estimating the case-fatality risk (CFR)—the probability that a person dies from an infection given that they are a case—is a high priority in epidemiologic investigation of newly emerging infectious diseases and sometimes in new outbreaks of known infectious diseases. The data available to estimate the overall CFR are often gathered for other purposes (e.g., surveillance) in challenging circumstances. We describe two forms of bias that may affect the estimation of the overall CFR—preferential ascertainment of severe cases and bias from reporting delays—and review solutions that have been proposed and implemented in past epidemics. Also of interest is the estimation of the causal impact of specific interventions (e.g., hospitalization, or hospitalization at a particular hospital) on survival, which can be estimated as a relative CFR for two or more groups. When observational data are used for this purpose, three more sources of bias may arise: confounding, survivorship bias, and selection due to preferential inclusion in surveillance datasets of those who are hospitalized and/or die. We illustrate these biases and caution against causal interpretation of differential CFR among those receiving different interventions in observational datasets. Again, we discuss ways to reduce these biases, particularly by estimating outcomes in smaller but more systematically defined cohorts ascertained before the onset of symptoms, such as those identified by forward contact tracing. Finally, we discuss the circumstances in which these biases may affect non-causal interpretation of risk factors for death among cases. PMID:26181387
BACKGROUND RADIATION MEASUREMENTS AND CANCER RISK ESTIMATES FOR SEBINKARAHISAR, TURKEY.
Kurnaz, Asli
2013-07-19
This paper presents the measurement results of environmental radioactivity levels for Şebinkarahisar district (uranium-thorium area), Giresun, Turkey. The radioactivity concentrations of (238)U, (232)Th, (40)K and the fission product (137)Cs in soil samples collected from 73 regions from the surroundings of the study area were determined. In situ measurements of the gamma dose rate in air were performed in the same 73 locations where the soil samples were collected using a portable NaI detector. Also the mean radioactivity concentrations of (238)U, (232)Th and (40)K in rock samples collected from 50 regions were determined. The mean estimated cancer risk value was found. The seasonal variations of the indoor radon activity concentrations were determined in the 30 dwellings in the study area. In addition, the mean gross alpha, gross beta and radon activities in tap water samples were determined in the same 30 dwellings. The excess lifetime cancer risk was calculated using the risk factors of International Commission on Radiological Protection and Biological Effects of Ionizing Radiation. Radiological maps of the Şebinkarahisar region were composed using the results obtained from this study.
Abramowitz, Joelle; O'Hara, Brett; Morris, Darcy Steeg
2017-04-01
This paper considers the risk of incurring future medical expenditures in light of a family's resources available to pay for those expenditures as well as their choice of health insurance. We model non-premium medical out-of-pocket expenditures and use the estimates from our model to develop a prospective measure of medical care economic risk estimating the proportion of families who are at risk of incurring high non-premium out-of-pocket medical care expenses in relation to its resources. We further use the estimates from our model to compare the extent to which different types of insurance mitigate the risk of incurring non-premium expenditures by providing for increased utilization of medical care. We find that while 21.3% of families lack the resources to pay for the median expenditures for their insurance type, 42.4% lack the resources to pay for the 99(th) percentile of expenditures for their insurance type. We also find the mediating effect of insurance on non-premium expenditures to outweigh the associated premium expense for expenditures above $1804 for employer-sponsored insurance and $4337 for direct purchase insurance for those younger than age 65; and above $12 118 of expenditures for Medicare supplementary plans for those aged 65 or older. Published 2016. This article is a U.S. Government work and is in the public domain in the USA.
Pensado, Osvaldo; Mancillas, James
2007-07-01
An approach is described to estimate mean consequences and confidence bounds on the mean of seismic events with low probability of breaching components of the engineered barrier system. The approach is aimed at complementing total system performance assessment models used to understand consequences of scenarios leading to radionuclide releases in geologic nuclear waste repository systems. The objective is to develop an efficient approach to estimate mean consequences associated with seismic events of low probability, employing data from a performance assessment model with a modest number of Monte Carlo realizations. The derived equations and formulas were tested with results from a specific performance assessment model. The derived equations appear to be one method to estimate mean consequences without having to use a large number of realizations. (authors)
Risk Estimates and Risk Factors Related to Psychiatric Inpatient Suicide—An Overview
Madsen, Trine; Erlangsen, Annette; Nordentoft, Merete
2017-01-01
People with mental illness have an increased risk of suicide. The aim of this paper is to provide an overview of suicide risk estimates among psychiatric inpatients based on the body of evidence found in scientific peer-reviewed literature; primarily focusing on the relative risks, rates, time trends, and socio-demographic and clinical risk factors of suicide in psychiatric inpatients. Psychiatric inpatients have a very high risk of suicide relative to the background population, but it remains challenging for clinicians to identify those patients that are most likely to die from suicide during admission. Most studies are based on low power, thus compromising quality and generalisability. The few studies with sufficient statistical power mainly identified non-modifiable risk predictors such as male gender, diagnosis, or recent deliberate self-harm. Also, the predictive value of these predictors is low. It would be of great benefit if future studies would be based on large samples while focusing on modifiable predictors over the course of an admission, such as hopelessness, depressive symptoms, and family/social situations. This would improve our chances of developing better risk assessment tools. PMID:28257103
Risk Estimates and Risk Factors Related to Psychiatric Inpatient Suicide-An Overview.
Madsen, Trine; Erlangsen, Annette; Nordentoft, Merete
2017-03-02
People with mental illness have an increased risk of suicide. The aim of this paper is to provide an overview of suicide risk estimates among psychiatric inpatients based on the body of evidence found in scientific peer-reviewed literature; primarily focusing on the relative risks, rates, time trends, and socio-demographic and clinical risk factors of suicide in psychiatric inpatients. Psychiatric inpatients have a very high risk of suicide relative to the background population, but it remains challenging for clinicians to identify those patients that are most likely to die from suicide during admission. Most studies are based on low power, thus compromising quality and generalisability. The few studies with sufficient statistical power mainly identified non-modifiable risk predictors such as male gender, diagnosis, or recent deliberate self-harm. Also, the predictive value of these predictors is low. It would be of great benefit if future studies would be based on large samples while focusing on modifiable predictors over the course of an admission, such as hopelessness, depressive symptoms, and family/social situations. This would improve our chances of developing better risk assessment tools.
Ellison, L.E.; O'Shea, T.J.; Neubaum, D.J.; Neubaum, M.A.; Pearce, R.D.; Bowen, R.A.
2007-01-01
We compared conventional capture (primarily mist nets and harp traps) and passive integrated transponder (PIT) tagging techniques for estimating capture and survival probabilities of big brown bats (Eptesicus fuscus) roosting in buildings in Fort Collins, Colorado. A total of 987 female adult and juvenile bats were captured and marked by subdermal injection of PIT tags during the summers of 2001-2005 at five maternity colonies in buildings. Openings to roosts were equipped with PIT hoop-style readers, and exit and entry of bats were passively monitored on a daily basis throughout the summers of 2002-2005. PIT readers 'recaptured' adult and juvenile females more often than conventional capture events at each roost. Estimates of annual capture probabilities for all five colonies were on average twice as high when estimated from PIT reader data (P?? = 0.93-1.00) than when derived from conventional techniques (P?? = 0.26-0.66), and as a consequence annual survival estimates were more precisely estimated when using PIT reader encounters. Short-term, daily capture estimates were also higher using PIT readers than conventional captures. We discuss the advantages and limitations of using PIT tags and passive encounters with hoop readers vs. conventional capture techniques for estimating these vital parameters in big brown bats. ?? Museum and Institute of Zoology PAS.
Huang, Biao; Zhao, Yongcun
2014-01-01
Estimating standard-exceeding probabilities of toxic metals in soil is crucial for environmental evaluation. Because soil pH and land use types have strong effects on the bioavailability of trace metals in soil, they were taken into account by some environmental protection agencies in making composite soil environmental quality standards (SEQSs) that contain multiple metal thresholds under different pH and land use conditions. This study proposed a method for estimating the standard-exceeding probability map of soil cadmium using a composite SEQS. The spatial variability and uncertainty of soil pH and site-specific land use type were incorporated through simulated realizations by sequential Gaussian simulation. A case study was conducted using a sample data set from a 150 km2 area in Wuhan City and the composite SEQS for cadmium, recently set by the State Environmental Protection Administration of China. The method may be useful for evaluating the pollution risks of trace metals in soil with composite SEQSs. PMID:24672364
Qu, Mingkai; Li, Weidong; Zhang, Chuanrong; Huang, Biao; Zhao, Yongcun
2014-01-01
Estimating standard-exceeding probabilities of toxic metals in soil is crucial for environmental evaluation. Because soil pH and land use types have strong effects on the bioavailability of trace metals in soil, they were taken into account by some environmental protection agencies in making composite soil environmental quality standards (SEQSs) that contain multiple metal thresholds under different pH and land use conditions. This study proposed a method for estimating the standard-exceeding probability map of soil cadmium using a composite SEQS. The spatial variability and uncertainty of soil pH and site-specific land use type were incorporated through simulated realizations by sequential Gaussian simulation. A case study was conducted using a sample data set from a 150 km(2) area in Wuhan City and the composite SEQS for cadmium, recently set by the State Environmental Protection Administration of China. The method may be useful for evaluating the pollution risks of trace metals in soil with composite SEQSs.
Daly, Megan E.; Luxton, Gary; Choi, Clara Y.H.; Gibbs, Iris C.; Chang, Steven D.; Adler, John R.; Soltys, Scott G.
2012-04-01
Purpose: To determine whether normal tissue complication probability (NTCP) analyses of the human spinal cord by use of the Lyman-Kutcher-Burman (LKB) model, supplemented by linear-quadratic modeling to account for the effect of fractionation, predict the risk of myelopathy from stereotactic radiosurgery (SRS). Methods and Materials: From November 2001 to July 2008, 24 spinal hemangioblastomas in 17 patients were treated with SRS. Of the tumors, 17 received 1 fraction with a median dose of 20 Gy (range, 18-30 Gy) and 7 received 20 to 25 Gy in 2 or 3 sessions, with cord maximum doses of 22.7 Gy (range, 17.8-30.9 Gy) and 22.0 Gy (range, 20.2-26.6 Gy), respectively. By use of conventional values for {alpha}/{beta}, volume parameter n, 50% complication probability dose TD{sub 50}, and inverse slope parameter m, a computationally simplified implementation of the LKB model was used to calculate the biologically equivalent uniform dose and NTCP for each treatment. Exploratory calculations were performed with alternate values of {alpha}/{beta} and n. Results: In this study 1 case (4%) of myelopathy occurred. The LKB model using radiobiological parameters from Emami and the logistic model with parameters from Schultheiss overestimated complication rates, predicting 13 complications (54%) and 18 complications (75%), respectively. An increase in the volume parameter (n), to assume greater parallel organization, improved the predictive value of the models. Maximum-likelihood LKB fitting of {alpha}/{beta} and n yielded better predictions (0.7 complications), with n = 0.023 and {alpha}/{beta} = 17.8 Gy. Conclusions: The spinal cord tolerance to the dosimetry of SRS is higher than predicted by the LKB model using any set of accepted parameters. Only a high {alpha}/{beta} value in the LKB model and only a large volume effect in the logistic model with Schultheiss data could explain the low number of complications observed. This finding emphasizes that radiobiological models
Declining bioavailability and inappropriate estimation of risk of persistent compounds
Kelsey, J.W.; Alexander, M.
1997-03-01
Earthworms (Eisenia foetida) assimilated decreasing amounts of atrazine, phenanthrene, and naphthalene that had been incubated for increasing periods of time in sterile soil. The amount of atrazine and phenanthrene removed from soil by mild extractants also decreased with time. The declines in bioavailability of the three compounds to earthworms and of naphthalene to bacteria were not reflected by analysis involving vigorous methods of solvent extraction; similar results for bioavailability of phenanthrene and 4-nitrophenol to bacteria were obtained in a previous study conducted at this laboratory. The authors suggest that regulations based on vigorous extractions for the analyses of persistent organic pollutants in soil do not appropriately estimate exposure or risk to susceptible populations.
A Multibiomarker-Based Model for Estimating the Risk of Septic Acute Kidney Injury
Wong, Hector R.; Cvijanovich, Natalie Z.; Anas, Nick; Allen, Geoffrey L.; Thomas, Neal J.; Bigham, Michael T.; Weiss, Scott L.; Fitzgerald, Julie; Checchia, Paul A.; Meyer, Keith; Shanley, Thomas P.; Quasney, Michael; Hall, Mark; Gedeit, Rainer; Freishtat, Robert J.; Nowak, Jeffrey; Raj, Shekhar S.; Gertz, Shira; Dawson, Emily; Howard, Kelli; Harmon, Kelli; Lahni, Patrick; Frank, Erin; Hart, Kimberly W.; Lindsell, Christopher J.
2015-01-01
Objective The development of acute kidney injury in patients with sepsis is associated with worse outcomes. Identifying those at risk for septic acute kidney injury could help to inform clinical decision making. We derived and tested a multibiomarker-based model to estimate the risk of septic acute kidney injury in children with septic shock. Design Candidate serum protein septic acute kidney injury biomarkers were identified from previous transcriptomic studies. Model derivation involved measuring these biomarkers in serum samples from 241 subjects with septic shock obtained during the first 24 hours of admission and then using a Classification and Regression Tree approach to estimate the probability of septic acute kidney injury 3 days after the onset of septic shock, defined as at least two-fold increase from baseline serum creatinine. The model was then tested in a separate cohort of 200 subjects. Setting Multiple PICUs in the United States. Interventions None other than standard care. Measurements and Main Results The decision tree included a first-level decision node based on day 1 septic acute kidney injury status and five subsequent biomarker-based decision nodes. The area under the curve for the tree was 0.95 (CI95, 0.91–0.99), with a sensitivity of 93% and a specificity of 88%. The tree was superior to day 1 septic acute kidney injury status alone for estimating day 3 septic acute kidney injury risk. In the test cohort, the tree had an area under the curve of 0.83 (0.72–0.95), with a sensitivity of 85% and a specificity of 77% and was also superior to day 1 septic acute kidney injury status alone for estimating day 3 septic acute kidney injury risk. Conclusions We have derived and tested a model to estimate the risk of septic acute kidney injury on day 3 of septic shock using a novel panel of biomarkers. The model had very good performance in a test cohort and has test characteristics supporting clinical utility and further prospective evaluation
Uncertainties in estimating health risks associated with exposure to ionising radiation.
Preston, R Julian; Boice, John D; Brill, A Bertrand; Chakraborty, Ranajit; Conolly, Rory; Hoffman, F Owen; Hornung, Richard W; Kocher, David C; Land, Charles E; Shore, Roy E; Woloschak, Gayle E
2013-09-01
The information for the present discussion on the uncertainties associated with estimation of radiation risks and probability of disease causation was assembled for the recently published NCRP Report No. 171 on this topic. This memorandum provides a timely overview of the topic, given that quantitative uncertainty analysis is the state of the art in health risk assessment and given its potential importance to developments in radiation protection. Over the past decade the increasing volume of epidemiology data and the supporting radiobiology findings have aided in the reduction of uncertainty in the risk estimates derived. However, it is equally apparent that there remain significant uncertainties related to dose assessment, low dose and low dose-rate extrapolation approaches (e.g. the selection of an appropriate dose and dose-rate effectiveness factor), the biological effectiveness where considerations of the health effects of high-LET and lower-energy low-LET radiations are required and the transfer of risks from a population for which health effects data are available to one for which such data are not available. The impact of radiation on human health has focused in recent years on cancer, although there has been a decided increase in the data for noncancer effects together with more reliable estimates of the risk following radiation exposure, even at relatively low doses (notably for cataracts and cardiovascular disease). New approaches for the estimation of hereditary risk have been developed with the use of human data whenever feasible, although the current estimates of heritable radiation effects still are based on mouse data because of an absence of effects in human studies. Uncertainties associated with estimation of these different types of health effects are discussed in a qualitative and semi-quantitative manner as appropriate. The way forward would seem to require additional epidemiological studies, especially studies of low dose and low dose
Model stimulations to estimate malaria risk under climate change.
Jetten, T H; Martens, W J; Takken, W
1996-05-01
The current geographic range of malaria is much smaller than its potential range. In many regions there exists a phenomena characterized as "Anophelism without malaria." The vectors are present but malaria transmission does not occur. Vectorial capacity often has been used as a parameter to estimate the susceptibility of an area to malaria. Model computations with global climatological data show that a dynamic concept of vectorial capacity can be used as a comparative risk indicator to predict the current extent and distribution of malarious regions in the world. A sensitivity analysis done in 3 distinct geographic areas shows that the areas of largest change of epidemic potential caused by a temperature increase are those where mosquitoes already occur but where development of the parasite is limited by temperature. Computations with the model presented here predict, with different climate scenarios, an increased malaria risk in areas bordering malaria endemic regions and at higher altitudes within malarious regions under a temperature increase of 2-4 degrees C.
Gambling disorder: estimated prevalence rates and risk factors in Macao.
Wu, Anise M S; Lai, Mark H C; Tong, Kwok-Kit
2014-12-01
An excessive, problematic gambling pattern has been regarded as a mental disorder in the Diagnostic and Statistical Manual for Mental Disorders (DSM) for more than 3 decades (American Psychiatric Association [APA], 1980). In this study, its latest prevalence in Macao (one of very few cities with legalized gambling in China and the Far East) was estimated with 2 major changes in the diagnostic criteria, suggested by the 5th edition of DSM (APA, 2013): (a) removing the "Illegal Act" criterion, and (b) lowering the threshold for diagnosis. A random, representative sample of 1,018 Macao residents was surveyed with a phone poll design in January 2013. After the 2 changes were adopted, the present study showed that the estimated prevalence rate of gambling disorder was 2.1% of the Macao adult population. Moreover, the present findings also provided empirical support to the application of these 2 recommended changes when assessing symptoms of gambling disorder among Chinese community adults. Personal risk factors of gambling disorder, namely being male, having low education, a preference for casino gambling, as well as high materialism, were identified.
From mechanisms to risk estimation--bridging the chasm.
Curtis, S B; Hazelton, W D; Luebeck, E G; Moolgavkar, S H
2004-01-01
We have a considerable amount of work ahead of us to determine the importance of the wealth of new information emerging in the fields of sub-cellular, cellular and tissue biology in order to improve the estimation of radiation risk at low dose and protracted dose-rate. In this paper, we suggest that there is a need to develop models of the specific health effects of interest (e.g., carcinogenesis in specific tissues), which embody as much of the mechanistic (i.e., biological) information as is deemed necessary. Although it is not realistic to expect that every radiation-induced process should or could be included, we can hope that the major factors that shape the time dependence of evolution of damage can be identified and quantified to the point where reasonable estimations of risk can be made. Regarding carcinogenesis in particular, the structure of the model itself plays a role in determining the relative importance of various processes. We use a specific form of a multi-stage carcinogenic model to illustrate this point. We show in a review of the application of this model to lung cancer incidence and mortality in two exposed populations that for both high- and low-LET radiation, there is evidence of an "inverse dose-rate" or protraction effect. This result could be of some considerable importance, because it would imply that risk from protracted exposure even to low-LET radiation might be greater than from acute exposure, an opinion not currently held in the radiation protection community. This model also allows prediction of the evolution of the risk over the lifetimes of the exposed individuals. One inference is that radiation-induced initiation (i.e., the first cellular carcinogenic event(s) occurring in normal tissue after the passage of the radiation) may not be the driving factor in the risk, but more important may be the effects of the radiation on already-initiated cells in the tissue. Although present throughout the length of the exposure, radiation
Estimating the Risk of Renal Stone Events During Long-Duration Spaceflight
NASA Technical Reports Server (NTRS)
Reyes, David; Kerstman, Eric; Locke, James
2014-01-01
Introduction: Given the bone loss and increased urinary calcium excretion in the microgravity environment, persons participating in long-duration spaceflight may have an increased risk for renal stone formation. Renal stones are often an incidental finding of abdominal imaging studies done for other reasons. Thus, some crewmembers may have undiscovered, asymptomatic stones prior to their mission. Methods: An extensive literature search was conducted concerning the natural history of asymptomatic renal stones. For comparison, simulations were done using the Integrated Medical Model (IMM). The IMM is an evidence-based decision support tool that provides risk analysis and has the capability to optimize medical systems for missions by minimizing the occurrence of adverse mission outcomes such as evacuation and loss of crew life within specified mass and volume constraints. Results: The literature of the natural history of asymptomatic renal stones in the general medical population shows that the probability of symptomatic event is 8% to 34% at 1 to 3 years for stones < 7 mm. Extrapolated to a 6-month mission, for stones < 5 to 7 mm, the risk for any stone event is about 4 to 6%, with a 0.7% to 4% risk for intervention, respectively. IMM simulations compare favorably with risk estimates garnered from the terrestrial literature. The IMM forecasts that symptomatic renal stones may be one of the top drivers for medical evacuation of an International Space Station (ISS) mission. Discussion: Although the likelihood of a stone event is low, the consequences could be severe due to limitations of current ISS medical capabilities. Therefore, these risks need to be quantified to aid planning, limit crew morbidity and mitigate mission impacts. This will be especially critical for missions beyond earth orbit, where evacuation may not be an option.
Estimating the Risk of Renal Stone Events during Long-Duration Spaceflight
NASA Technical Reports Server (NTRS)
Reyes, David; Kerstman, Eric; Gray, Gary; Locke, James
2014-01-01
Introduction: Given the bone loss and increased urinary calcium excretion in the microgravity environment, persons participating in long-duration spaceflight may have an increased risk for renal stone formation. Renal stones are often an incidental finding of abdominal imaging studies done for other reasons. Thus, some crewmembers may have undiscovered, asymptomatic stones prior to their mission. Methods: An extensive literature search was conducted concerning the natural history of asymptomatic renal stones. For comparison, simulations were done using the Integrated Medical Model (IMM). The IMM is an evidence-based decision support tool that provides risk analysis and has the capability to optimize medical systems for missions by minimizing the occurrence of adverse mission outcomes such as evacuation and loss of crew life within specified mass and volume constraints. Results: The literature of the natural history of asymptomatic renal stones in the general medical population shows that the probability of symptomatic event is 8% to 34% at 1 to 3 years for stones < 7 mm. Extrapolated to a 6-month mission, for stones < 5 to 7 mm, the risk for any stone event is about 4 to 6%, with a 0.7% to 4% risk for intervention, respectively. IMM simulations compare favorably with risk estimates garnered from the terrestrial literature. The IMM forecasts that symptomatic renal stones may be one of the top drivers for medical evacuation of an International Space Station (ISS) mission. Discussion: Although the likelihood of a stone event is low, the consequences could be severe due to limitations of current ISS medical capabilities. Therefore, these risks need to be quantified to aid planning, limit crew morbidity and mitigate mission impacts. This will be especially critical for missions beyond earth orbit, where evacuation may not be an option.
Fritz, Stacy; Middleton, Addie; Allison, Leslie; Wingood, Mariana; Phillips, Emma; Criss, Michelle; Verma, Sangita; Osborne, Jackie; Chui, Kevin K.
2017-01-01
Background: Falls and their consequences are significant concerns for older adults, caregivers, and health care providers. Identification of fall risk is crucial for appropriate referral to preventive interventions. Falls are multifactorial; no single measure is an accurate diagnostic tool. There is limited information on which history question, self-report measure, or performance-based measure, or combination of measures, best predicts future falls. Purpose: First, to evaluate the predictive ability of history questions, self-report measures, and performance-based measures for assessing fall risk of community-dwelling older adults by calculating and comparing posttest probability (PoTP) values for individual test/measures. Second, to evaluate usefulness of cumulative PoTP for measures in combination. Data Sources: To be included, a study must have used fall status as an outcome or classification variable, have a sample size of at least 30 ambulatory community-living older adults (≥65 years), and track falls occurrence for a minimum of 6 months. Studies in acute or long-term care settings, as well as those including participants with significant cognitive or neuromuscular conditions related to increased fall risk, were excluded. Searches of Medline/PubMED and Cumulative Index of Nursing and Allied Health (CINAHL) from January 1990 through September 2013 identified 2294 abstracts concerned with fall risk assessment in community-dwelling older adults. Study Selection: Because the number of prospective studies of fall risk assessment was limited, retrospective studies that classified participants (faller/nonfallers) were also included. Ninety-five full-text articles met inclusion criteria; 59 contained necessary data for calculation of PoTP. The Quality Assessment Tool for Diagnostic Accuracy Studies (QUADAS) was used to assess each study's methodological quality. Data Extraction: Study design and QUADAS score determined the level of evidence. Data for calculation
NASA Astrophysics Data System (ADS)
Siettos, Constantinos I.; Anastassopoulou, Cleo; Russo, Lucia; Grigoras, Christos; Mylonakis, Eleftherios
2016-06-01
Based on multiscale agent-based computations we estimated the per-contact probability of transmission by age of the Ebola virus disease (EVD) that swept through Liberia from May 2014 to March 2015. For the approximation of the epidemic dynamics we have developed a detailed agent-based model with small-world interactions between individuals categorized by age. For the estimation of the structure of the evolving contact network as well as the per-contact transmission probabilities by age group we exploited the so called Equation-Free framework. Model parameters were fitted to official case counts reported by the World Health Organization (WHO) as well as to recently published data of key epidemiological variables, such as the mean time to death, recovery and the case fatality rate.
Cho, Hyunyi; Shen, Lijiang; Wilson, Kari M
2013-03-01
Perceived lack of realism in alcohol advertising messages promising positive outcomes and antialcohol and antidrug messages portraying negative outcomes of alcohol consumption has been a cause for public health concern. This study examined the effects of perceived realism dimensions on personal probability estimation through identification and message minimization. Data collected from college students in U.S. Midwest in 2010 (N = 315) were analyzed with multilevel structural equation modeling. Plausibility and narrative consistency mitigated message minimization, but they did not influence identification. Factuality and perceptual quality influenced both message minimization and identification, but their effects were smaller than those of typicality. Typicality was the strongest predictor of probability estimation. Implications of the results and suggestions for future research are provided.
ESTIMATING RISK TO CALIFORNIA ENERGY INFRASTRUCTURE FROM PROJECTED CLIMATE CHANGE
Sathaye, Jayant; Dale, Larry; Larsen, Peter; Fitts, Gary; Koy, Kevin; Lewis, Sarah; Lucena, Andre
2011-06-22
This report outlines the results of a study of the impact of climate change on the energy infrastructure of California and the San Francisco Bay region, including impacts on power plant generation; transmission line and substation capacity during heat spells; wildfires near transmission lines; sea level encroachment upon power plants, substations, and natural gas facilities; and peak electrical demand. Some end-of-century impacts were projected:Expected warming will decrease gas-fired generator efficiency. The maximum statewide coincident loss is projected at 10.3 gigawatts (with current power plant infrastructure and population), an increase of 6.2 percent over current temperature-induced losses. By the end of the century, electricity demand for almost all summer days is expected to exceed the current ninetieth percentile per-capita peak load. As much as 21 percent growth is expected in ninetieth percentile peak demand (per-capita, exclusive of population growth). When generator losses are included in the demand, the ninetieth percentile peaks may increase up to 25 percent. As the climate warms, California's peak supply capacity will need to grow faster than the population.Substation capacity is projected to decrease an average of 2.7 percent. A 5C (9F) air temperature increase (the average increase predicted for hot days in August) will diminish the capacity of a fully-loaded transmission line by an average of 7.5 percent.The potential exposure of transmission lines to wildfire is expected to increase with time. We have identified some lines whose probability of exposure to fire are expected to increase by as much as 40 percent. Up to 25 coastal power plants and 86 substations are at risk of flooding (or partial flooding) due to sea level rise.
Oldenburg, Curtis M.; Budnitz, Robert J.
2016-08-31
If Carbon dioxide Capture and Storage (CCS) is to be effective in mitigating climate change, it will need to be carried out on a very large scale. This will involve many thousands of miles of dedicated high-pressure pipelines in order to transport many millions of tonnes of CO_{2} annually, with the CO_{2} delivered to many thousands of wells that will inject the CO_{2} underground. The new CCS infrastructure could rival in size the current U.S. upstream natural gas pipeline and well infrastructure. This new infrastructure entails hazards for life, health, animals, the environment, and natural resources. Pipelines are known to rupture due to corrosion, from external forces such as impacts by vehicles or digging equipment, by defects in construction, or from the failure of valves and seals. Similarly, wells are vulnerable to catastrophic failure due to corrosion, cement degradation, or operational mistakes. While most accidents involving pipelines and wells will be minor, there is the inevitable possibility of accidents with very high consequences, especially to public health. The most important consequence of concern is CO_{2} release to the environment in concentrations sufficient to cause death by asphyxiation to nearby populations. Such accidents are thought to be very unlikely, but of course they cannot be excluded, even if major engineering effort is devoted (as it will be) to keeping their probability low and their consequences minimized. This project has developed a methodology for analyzing the risks of these rare but high-consequence accidents, using a step-by-step probabilistic methodology. A key difference between risks for pipelines and wells is that the former are spatially distributed along the pipe whereas the latter are confined to the vicinity of the well. Otherwise, the methodology we develop for risk assessment of pipeline and well failures is similar and provides an analysis both of the annual probabilities of
Carstens, Bryan C; Knowles, L Lacey
2007-06-01
Estimating phylogenetic relationships among closely related species can be extremely difficult when there is incongruence among gene trees and between the gene trees and the species tree. Here we show that incorporating a model of the stochastic loss of gene lineages by genetic drift into the phylogenetic estimation procedure can provide a robust estimate of species relationships, despite widespread incomplete sorting of ancestral polymorphism. This approach is applied to a group of montane Melanoplus grasshoppers for which genealogical discordance among loci and incomplete lineage sorting obscures any obvious phylogenetic relationships among species. Unlike traditional treatments where gene trees estimated using standard phylogenetic methods are implicitly equated with the species tree, with the coalescent-based approach the species tree is modeled probabilistically from the estimated gene trees. The estimated species phylogeny (the ESP) is calculated for the grasshoppers from multiple gene trees reconstructed for nuclear loci and a mitochondrial gene. This empirical application is coupled with a simulation study to explore the performance of the coalescent-based approach. Specifically, we test the accuracy of the ESP given the data based on analyses of simulated data matching the multilocus data collected in Melanoplus (i.e., data were simulated for each locus with the same number of base pairs and locus-specific mutational models). The results of the study show that ESPs can be computed using the coalescent-based approach long before reciprocal monophyly has been achieved, and that these statistical estimates are accurate. This contrasts with analyses of the empirical data collected in Melanoplus and simulated data based on concatenation of multiple loci, for which the incomplete lineage sorting of recently diverged species posed significant problems. The strengths and potential challenges associated with incorporating an explicit model of gene
Biokinetic and dosimetric modelling in the estimation of radiation risks from internal emitters.
Harrison, John
2009-06-01
The International Commission on Radiological Protection (ICRP) has developed biokinetic and dosimetric models that enable the calculation of organ and tissue doses for a wide range of radionuclides. These are used to calculate equivalent and effective dose coefficients (dose in Sv Bq(-1) intake), considering occupational and environmental exposures. Dose coefficients have also been given for a range of radiopharmaceuticals used in diagnostic medicine. Using equivalent and effective dose, exposures from external sources and from different radionuclides can be summed for comparison with dose limits, constraints and reference levels that relate to risks from whole-body radiation exposure. Risk estimates are derived largely from follow-up studies of the survivors of the atomic bombings at Hiroshima and Nagasaki in 1945. New dose coefficients will be required following the publication in 2007 of new ICRP recommendations. ICRP biokinetic and dosimetric models are subject to continuing review and improvement, although it is arguable that the degree of sophistication of some of the most recent models is greater than required for the calculation of effective dose to a reference person for the purposes of regulatory control. However, the models are also used in the calculation of best estimates of doses and risks to individuals, in epidemiological studies and to determine probability of cancer causation. Models are then adjusted to best fit the characteristics of the individuals and population under consideration. For example, doses resulting from massive discharges of strontium-90 and other radionuclides to the Techa River from the Russian Mayak plutonium plant in the early years of its operation are being estimated using models adapted to take account of measurements on local residents and other population-specific data. Best estimates of doses to haemopoietic bone marrow, in utero and postnatally, are being used in epidemiological studies of radiation-induced leukaemia
Ssematimba, Amos; Elbers, Armin R. W.; Hagenaars, Thomas J.; de Jong, Mart C. M.
2012-01-01
Estimates of the per-contact probability of transmission between farms of Highly Pathogenic Avian Influenza virus of H7N7 subtype during the 2003 epidemic in the Netherlands are important for the design of better control and biosecurity strategies. We used standardized data collected during the epidemic and a model to extract data for untraced contacts based on the daily number of infectious farms within a given distance of a susceptible farm. With these data, we used a maximum likelihood estimation approach to estimate the transmission probabilities by the individual contact types, both traced and untraced. The estimated conditional probabilities, conditional on the contact originating from an infectious farm, of virus transmission were: 0.000057 per infectious farm within 1 km per day, 0.000413 per infectious farm between 1 and 3 km per day, 0.0000895 per infectious farm between 3 and 10 km per day, 0.0011 per crisis organisation contact, 0.0414 per feed delivery contact, 0.308 per egg transport contact, 0.133 per other-professional contact and, 0.246 per rendering contact. We validate these outcomes against literature data on virus genetic sequences for outbreak farms. These estimates can be used to inform further studies on the role that improved biosecurity between contacts and/or contact frequency reduction can play in eliminating between-farm spread of the virus during future epidemics. The findings also highlight the need to; 1) understand the routes underlying the infections without traced contacts and, 2) to review whether the contact-tracing protocol is exhaustive in relation to all the farm’s day-to-day activities and practices. PMID:22808285
Stevens, Michael R.; Flynn, Jennifer L.; Stephens, Verlin C.; Verdin, Kristine L.
2011-01-01
During 2009, the U.S. Geological Survey, in cooperation with Gunnison County, initiated a study to estimate the potential for postwildfire debris flows to occur in the drainage basins occupied by Carbonate, Slate, Raspberry, and Milton Creeks near Marble, Colorado. Currently (2010), these drainage basins are unburned but could be burned by a future wildfire. Empirical models derived from statistical evaluation of data collected from recently burned basins throughout the intermountain western United States were used to estimate the probability of postwildfire debris-flow occurrence and debris-flow volumes for drainage basins occupied by Carbonate, Slate, Raspberry, and Milton Creeks near Marble. Data for the postwildfire debris-flow models included drainage basin area; area burned and burn severity; percentage of burned area; soil properties; rainfall total and intensity for the 5- and 25-year-recurrence, 1-hour-duration-rainfall; and topographic and soil property characteristics of the drainage basins occupied by the four creeks. A quasi-two-dimensional floodplain computer model (FLO-2D) was used to estimate the spatial distribution and the maximum instantaneous depth of the postwildfire debris-flow material during debris flow on the existing debris-flow fans that issue from the outlets of the four major drainage basins. The postwildfire debris-flow probabilities at the outlet of each drainage basin range from 1 to 19 percent for the 5-year-recurrence, 1-hour-duration rainfall, and from 3 to 35 percent for 25-year-recurrence, 1-hour-duration rainfall. The largest probabilities for postwildfire debris flow are estimated for Raspberry Creek (19 and 35 percent), whereas estimated debris-flow probabilities for the three other creeks range from 1 to 6 percent. The estimated postwildfire debris-flow volumes at the outlet of each creek range from 7,500 to 101,000 cubic meters for the 5-year-recurrence, 1-hour-duration rainfall, and from 9,400 to 126,000 cubic meters for
Rood, A S; McGavran, P D; Aanenson, J W; Till, J E
2001-08-01
Carbon tetrachloride is a degreasing agent that was used at the Rocky Flats Plant (RFP) in Colorado to clean product components and equipment. The chemical is considered a volatile organic compound and a probable human carcinogen. During the time the plant operated (1953-1989), most of the carbon tetrachloride was released to the atmosphere through building exhaust ducts. A smaller amount was released to the air via evaporation from open-air burn pits and ground-surface discharge points. Airborne releases from the plant were conservatively estimated to be equivalent to the amount of carbon tetrachloride consumed annually by the plant, which was estimated to be between 3.6 and 180 Mg per year. This assumption was supported by calculations that showed that most of the carbon tetrachloride discharged to the ground surface would subsequently be released to the atmosphere. Atmospheric transport of carbon tetrachloride from the plant to the surrounding community was estimated using a Gaussian Puff dispersion model (RATCHET). Time-integrated concentrations were estimated for nine hypothetical but realistic exposure scenarios that considered variation in lifestyle, location, age, and gender. Uncertainty distributions were developed for cancer slope factors and atmospheric dispersion factors. These uncertainties were propagated through to the final risk estimate using Monte Carlo techniques. The geometric mean risk estimates varied from 5.2 x 10(-6) for a hypothetical rancher or laborer working near the RFP to 3.4 x 10(-9) for an infant scenario. The distribution of incremental lifetime cancer incidence risk for the hypothetical rancher was between 1.3 x 10(-6) (5% value) and 2.1 x 10(-5) (95% value). These estimates are similar to or exceed estimated cancer risks posed by releases of radionuclides from the site.
R2 TRI facilities with 1999-2011 risk related estimates throughout the census blockgroup
This dataset delineates the distribution of estimate risk from the TRI facilities for 1999 - 2011 throughout the census blockgroup of the region using Office of Pollution, Prevention & Toxics (OPPT)'s Risk-Screening Environmental Indicators model (RSEI). The model uses the reported quantities of TRI releases of chemicals to estimate the impacts associated with each type of air release or transfer by every TRI facility.The RSEI was run to generate the estimate risk for each TRI facility in the region. The result from the model is joined to the TRI spatial data. Estimate risk values for each census block group were calculated based on the inverse distance of all the facilities which are within a 50 km radius of the census block group centroid. The estimate risk value for each census block group thus is an aggregated value that takes into account the