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 ...
ESTIMATION OF AGE TRANSITION PROBABILITIES.
ERIC Educational Resources Information Center
ZINTER, JUDITH R.
THIS NOTE DESCRIBES THE PROCEDURES USED IN DETERMINING DYNAMOD II AGE TRANSITION MATRICES. A SEPARATE MATRIX FOR EACH SEX-RACE GROUP IS DEVELOPED. THESE MATRICES WILL BE USED AS AN AID IN ESTIMATING THE TRANSITION PROBABILITIES IN THE LARGER DYNAMOD II MATRIX RELATING AGE TO OCCUPATIONAL CATEGORIES. THREE STEPS WERE USED IN THE PROCEDURE--(1)…
2016-07-01
A free mobile phone app has been launched providing nurses and other hospital clinicians with a simple way to identify high-risk surgical patients. The app is a phone version of the Surgical Outcome Risk Tool (SORT), originally developed for online use with computers by researchers from the National Confidential Enquiry into Patient Outcome and Death and the University College London Hospital Surgical Outcomes Research Centre. SORT uses information about patients' health and planned surgical procedures to estimate the risk of death within 30 days of an operation. The percentages are only estimates, taking into account the general risks of the procedures and some information about patients, and should not be confused with patient-specific estimates in individual cases. PMID:27369709
Dynamic probability estimator for machine learning.
Starzyk, Janusz A; Wang, Feng
2004-03-01
An efficient algorithm for dynamic estimation of probabilities without division on unlimited number of input data is presented. The method estimates probabilities of the sampled data from the raw sample count, while keeping the total count value constant. Accuracy of the estimate depends on the counter size, rather than on the total number of data points. Estimator follows variations of the incoming data probability within a fixed window size, without explicit implementation of the windowing technique. Total design area is very small and all probabilities are estimated concurrently. Dynamic probability estimator was implemented using a programmable gate array from Xilinx. The performance of this implementation is evaluated in terms of the area efficiency and execution time. This method is suitable for the highly integrated design of artificial neural networks where a large number of dynamic probability estimators can work concurrently. PMID:15384523
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
Webster, T.J.
1985-01-01
The discussion is divided into two parts. Part one is devoted to a review of the topic of assessing the likelihood of debt servicing difficulties by borrower nations by first tracing the growth of international bank lending activities by US commercial banks, followed by a general discussion of the international debt crisis and a brief survey of some of the conventional approaches employed by many international institutions to assess overseas lending risk. Part one continues with a survey of a variety of social, economic, and political considerations incorporated into the risk evaluation process and concludes with a discussion of how these factors are integrated into the microeconomics of international bank lending. Part two of this study discusses specifically the use of logit analysis as a tool for evaluating country risk under alternative subset data specifications. The paper concludes with a discussion of the possible presence of dynamic elements in the rescheduling process which may ultimately help to improve upon the predictive performance of the logit model.
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).
Modeling Finite-Time Failure Probabilities in Risk Analysis Applications.
Dimitrova, Dimitrina S; Kaishev, Vladimir K; Zhao, Shouqi
2015-10-01
In this article, we introduce a framework for analyzing the risk of systems failure based on estimating the failure probability. The latter is defined as the probability that a certain risk process, characterizing the operations of a system, reaches a possibly time-dependent critical risk level within a finite-time interval. Under general assumptions, we define two dually connected models for the risk process and derive explicit expressions for the failure probability and also the joint probability of the time of the occurrence of failure and the excess of the risk process over the risk level. We illustrate how these probabilistic models and results can be successfully applied in several important areas of risk analysis, among which are systems reliability, inventory management, flood control via dam management, infectious disease spread, and financial insolvency. Numerical illustrations are also presented. PMID:26010201
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.
Holmberg, Christine; Waters, Erika A.; Whitehouse, Katie; Daly, Mary; McCaskill-Stevens, Worta
2015-01-01
Background Decision making experts emphasize that understanding and using probabilistic information is important for making informed decisions about medical treatments involving complex risk-benefit tradeoffs. Yet empirical research demonstrates that individuals may not use probabilities when making decisions. Objectives To explore decision making and the use of probabilities for decision making from the perspective of women who were risk-eligible to enroll in the Study of Tamoxifen and Raloxifene (STAR). Methods We conducted narrative interviews with 20 women who agreed to participate in STAR and 20 women who declined. The project was based on a narrative approach. Analysis included the development of summaries of each narrative, and thematic analysis with developing a coding scheme inductively to code all transcripts to identify emerging themes. Results Interviewees explained and embedded their STAR decisions within experiences encountered throughout their lives. Such lived experiences included but were not limited to breast cancer family history, personal history of breast biopsies, and experiences or assumptions about taking tamoxifen or medicines more generally. Conclusions Women’s explanations of their decisions about participating in a breast cancer chemoprevention trial were more complex than decision strategies that rely solely on a quantitative risk-benefit analysis of probabilities derived from populations In addition to precise risk information, clinicians and risk communicators should recognize the importance and legitimacy of lived experience in individual decision making. PMID:26183166
Model estimates hurricane wind speed probabilities
NASA Astrophysics Data System (ADS)
Mumane, Richard J.; Barton, Chris; Collins, Eric; Donnelly, Jeffrey; Eisner, James; Emanuel, Kerry; Ginis, Isaac; Howard, Susan; Landsea, Chris; Liu, Kam-biu; Malmquist, David; McKay, Megan; Michaels, Anthony; Nelson, Norm; O Brien, James; Scott, David; Webb, Thompson, III
In the United States, intense hurricanes (category 3, 4, and 5 on the Saffir/Simpson scale) with winds greater than 50 m s -1 have caused more damage than any other natural disaster [Pielke and Pielke, 1997]. Accurate estimates of wind speed exceedance probabilities (WSEP) due to intense hurricanes are therefore of great interest to (re)insurers, emergency planners, government officials, and populations in vulnerable coastal areas.The historical record of U.S. hurricane landfall is relatively complete only from about 1900, and most model estimates of WSEP are derived from this record. During the 1899-1998 period, only two category-5 and 16 category-4 hurricanes made landfall in the United States. The historical record therefore provides only a limited sample of the most intense hurricanes.
Distributed estimation and joint probabilities estimation by entropy model
NASA Astrophysics Data System (ADS)
Fassinut-Mombot, B.; Zribi, M.; Choquel, J. B.
2001-05-01
This paper proposes the use of Entropy Model for distributed estimation system. Entropy Model is an entropic technique based on the minimization of conditional entropy and developed for Multi-Source/Sensor Information Fusion (MSIF) problem. We address the problem of distributed estimation from independent observations involving multiple sources, i.e., the problem of estimating or selecting one of several identity declaration, or hypothesis concerning an observed object. Two problems are considered in Entropy Model. In order to fuse observations using Entropy Model, it is necessary to know or estimate the conditional probabilities and by equivalent the joint probabilities. A common practice for estimating probability distributions from data when nothing is known (without a priori knowledge), one should prefer distributions that are as uniform as possible, that is, have maximal entropy. Next, the problem of combining (or ``fusing'') observations relating to identity hypotheses and selecting the most appropriate hypothesis about the object's identity is addressed. Much future work remains, but the results indicate that Entropy Model is a promising technique for distributed estimation. .
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
Radiation risk estimation models
Hoel, D.G.
1987-11-01
Cancer risk models and their relationship to ionizing radiation are discussed. There are many model assumptions and risk factors that have a large quantitative impact on the cancer risk estimates. Other health end points such as mental retardation may be an even more serious risk than cancer for those with in utero exposures. 8 references.
Estimating the Probability of Negative Events
ERIC Educational Resources Information Center
Harris, Adam J. L.; Corner, Adam; Hahn, Ulrike
2009-01-01
How well we are attuned to the statistics of our environment is a fundamental question in understanding human behaviour. It seems particularly important to be able to provide accurate assessments of the probability with which negative events occur so as to guide rational choice of preventative actions. One question that arises here is whether or…
Estimation of transition probabilities of credit ratings
NASA Astrophysics Data System (ADS)
Peng, Gan Chew; Hin, Pooi Ah
2015-12-01
The present research is based on the quarterly credit ratings of ten companies over 15 years taken from the database of the Taiwan Economic Journal. The components in the vector mi (mi1, mi2,⋯, mi10) may first be used to denote the credit ratings of the ten companies in the i-th quarter. The vector mi+1 in the next quarter is modelled to be dependent on the vector mi via a conditional distribution which is derived from a 20-dimensional power-normal mixture distribution. The transition probability Pkl (i ,j ) for getting mi+1,j = l given that mi, j = k is then computed from the conditional distribution. It is found that the variation of the transition probability Pkl (i ,j ) as i varies is able to give indication for the possible transition of the credit rating of the j-th company in the near future.
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
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.
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.
Classification criteria and probability risk maps: limitations and perspectives.
Saisana, Michaela; Dubois, Gregoire; Chaloulakou, Archontoula; Spyrellis, Nikolas
2004-03-01
Delineation of polluted zones with respect to regulatory standards, accounting at the same time for the uncertainty of the estimated concentrations, relies on classification criteria that can lead to significantly different pollution risk maps, which, in turn, can depend on the regulatory standard itself. This paper reviews four popular classification criteria related to the violation of a probability threshold or a physical threshold, using annual (1996-2000) nitrogen dioxide concentrations from 40 air monitoring stations in Milan. The relative advantages and practical limitations of each criterion are discussed, and it is shown that some of the criteria are more appropriate for the problem at hand and that the choice of the criterion can be supported by the statistical distribution of the data and/or the regulatory standard. Finally, the polluted area is estimated over the different years and concentration thresholds using the appropriate risk maps as an additional source of uncertainty. PMID:15046326
Radiations in space: risk estimates.
Fry, R J M
2002-01-01
The complexity of radiation environments in space makes estimation of risks more difficult than for the protection of terrestrial populations. In deep space the duration of the mission, position in the solar cycle, number and size of solar particle events (SPE) and the spacecraft shielding are the major determinants of risk. In low-earth orbit missions there are the added factors of altitude and orbital inclination. Different radiation qualities such as protons and heavy ions and secondary radiations inside the spacecraft such as neutrons of various energies, have to be considered. Radiation dose rates in space are low except for short periods during very large SPEs. Risk estimation for space activities is based on the human experience of exposure to gamma rays and to a lesser extent X rays. The doses of protons, heavy ions and neutrons are adjusted to take into account the relative biological effectiveness (RBE) of the different radiation types and thus derive equivalent doses. RBE values and factors to adjust for the effect of dose rate have to be obtained from experimental data. The influence of age and gender on the cancer risk is estimated from the data from atomic bomb survivors. Because of the large number of variables the uncertainities in the probability of the effects are large. Information needed to improve the risk estimates includes: (1) risk of cancer induction by protons, heavy ions and neutrons: (2) influence of dose rate and protraction, particularly on potential tissue effects such as reduced fertility and cataracts: and (3) possible effects of heavy ions on the central nervous system. Risk cannot be eliminated and thus there must be a consensus on what level of risk is acceptable. PMID:12382925
A Bayesian Estimator of Protein-Protein Association Probabilities
Gilmore, Jason M.; Auberry, Deanna L.; Sharp, Julia L.; White, Amanda M.; Anderson, Kevin K.; Daly, Don S.
2008-07-01
The Bayesian Estimator of Protein-Protein Association Probabilities (BEPro3) is a software tool for estimating probabilities of protein-protein association between bait and prey protein pairs using data from multiple-bait, multiple-replicate, protein pull-down LC-MS assay experiments. BEPro3 is open source software that runs on both Windows XP and Mac OS 10.4 or newer versions, and is freely available from http://www.pnl.gov/statistics/BEPro3.
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. PMID:25363706
Probability estimation in arithmetic and adaptive-Huffman entropy coders.
Duttweiler, D L; Chamzas, C
1995-01-01
Entropy coders, such as Huffman and arithmetic coders, achieve compression by exploiting nonuniformity in the probabilities under which a random variable to be coded takes on its possible values. Practical realizations generally require running adaptive estimates of these probabilities. An analysis of the relationship between estimation quality and the resulting coding efficiency suggests a particular scheme, dubbed scaled-count, for obtaining such estimates. It can optimally balance estimation accuracy against a need for rapid response to changing underlying statistics. When the symbols being coded are from a binary alphabet, simple hardware and software implementations requiring almost no computation are possible. A scaled-count adaptive probability estimator of the type described in this paper is used in the arithmetic coder of the JBIG and JPEG image coding standards. PMID:18289975
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. PMID:23383711
Interval estimation of small tail probabilities - applications in food safety.
Kedem, Benjamin; Pan, Lemeng; Zhou, Wen; Coelho, Carlos A
2016-08-15
Often in food safety and bio-surveillance it is desirable to estimate the probability that a contaminant or a function thereof exceeds an unsafe high threshold. The probability or chance in question is very small. To estimate such a probability, we need information about large values. In many cases, the data do not contain information about exceedingly large contamination levels, which ostensibly renders the problem insolvable. A solution is suggested whereby more information about small tail probabilities are obtained by combining the real data with computer-generated data repeatedly. This method provides short yet reliable interval estimates based on moderately large samples. An illustration is provided in terms of lead exposure data. Copyright © 2016 John Wiley & Sons, Ltd. PMID:26891189
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)
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.
Estimating the empirical probability of submarine landslide occurrence
Geist, Eric L.; Parsons, Thomas E.
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.
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. PMID:18267798
Bayesian Estimator of Protein-Protein Association Probabilities
Energy Science and Technology Software Center (ESTSC)
2008-05-28
The Bayesian Estimator of Protein-Protein Association Probabilities (BEPro3) is a software tool for estimating probabilities of protein-protein association between bait and prey protein pairs using data from multiple-bait, multiple-replicate, protein LC-MS/MS affinity isolation experiments. BEPro3 is public domain software, has been tested on Windows XP and version 10.4 or newer of the Mac OS 10.4, and is freely available. A user guide, example dataset with analysis and additional documentation are included with the BEPro3 download.
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.
Estimating Second Order Probability Beliefs from Subjective Survival Data
Hudomiet, Péter; Willis, Robert J.
2013-01-01
Based on subjective survival probability questions in the Health and Retirement Study (HRS), we use an econometric model to estimate the determinants of individual-level uncertainty about personal longevity. This model is built around the modal response hypothesis (MRH), a mathematical expression of the idea that survey responses of 0%, 50%, or 100% to probability questions indicate a high level of uncertainty about the relevant probability. We show that subjective survival expectations in 2002 line up very well with realized mortality of the HRS respondents between 2002 and 2010. We show that the MRH model performs better than typically used models in the literature of subjective probabilities. Our model gives more accurate estimates of low probability events and it is able to predict the unusually high fraction of focal 0%, 50%, and 100% answers observed in many data sets on subjective probabilities. We show that subjects place too much weight on parents’ age at death when forming expectations about their own longevity, whereas other covariates such as demographics, cognition, personality, subjective health, and health behavior are under weighted. We also find that less educated people, smokers, and women have less certain beliefs, and recent health shocks increase uncertainty about survival, too. PMID:24403866
Simulation and Estimation of Extreme Quantiles and Extreme Probabilities
Guyader, Arnaud; Hengartner, Nicolas; Matzner-Lober, Eric
2011-10-15
Let X be a random vector with distribution {mu} on Double-Struck-Capital-R {sup d} and {Phi} be a mapping from Double-Struck-Capital-R {sup d} to Double-Struck-Capital-R . That mapping acts as a black box, e.g., the result from some computer experiments for which no analytical expression is available. This paper presents an efficient algorithm to estimate a tail probability given a quantile or a quantile given a tail probability. The algorithm improves upon existing multilevel splitting methods and can be analyzed using Poisson process tools that lead to exact description of the distribution of the estimated probabilities and quantiles. The performance of the algorithm is demonstrated in a problem related to digital watermarking.
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.
Failure probability estimate of Type 304 stainless steel piping
Daugherty, W.L.; Awadalla, N.G.; Sindelar, R.L.; Mehta, H.S.; Ranganath, S.; General Electric Co., San Jose, CA )
1989-01-01
The primary source of in-service degradation of the SRS production reactor process water piping is intergranular stress corrosion cracking (IGSCC). IGSCC has occurred in a limited number of weld heat affected zones, areas known to be susceptible to IGSCC. A model has been developed to combine crack growth rates, crack size distributions, in-service examination reliability estimates and other considerations to estimate the pipe large-break frequency. This frequency estimates the probability that an IGSCC crack will initiate, escape detection by ultrasonic (UT) examination, and grow to instability prior to extending through-wall and being detected by the sensitive leak detection system. These events are combined as the product of four factors: (1) the probability that a given weld heat affected zone contains IGSCC, (2) the conditional probability, given the presence of IGSCC, that the cracking will escape detection during UT examination, (3) the conditional probability, given a crack escapes detection by UT, that it will not grow through-wall and be detected by leakage, and (4) the conditional probability, given a crack is not detected by leakage, that it grows to instability prior to the next UT exam. These four factors estimate the occurrence of several conditions that must coexist in order for a crack to lead to a large break of the process water piping. When evaluated for the SRS production reactors, they produce an extremely low break frequency. The objective of this paper is to present the assumptions, methodology, results and conclusions of a probabilistic evaluation for the direct failure of the primary coolant piping resulting from normal operation and seismic loads. This evaluation was performed to support the ongoing PRA effort and to complement deterministic analyses addressing the credibility of a double-ended guillotine break.
Revising probability estimates: Why increasing likelihood means increasing impact.
Maglio, Sam J; Polman, Evan
2016-08-01
Forecasted probabilities rarely stay the same for long. Instead, they are subject to constant revision-moving upward or downward, uncertain events become more or less likely. Yet little is known about how people interpret probability estimates beyond static snapshots, like a 30% chance of rain. Here, we consider the cognitive, affective, and behavioral consequences of revisions to probability forecasts. Stemming from a lay belief that revisions signal the emergence of a trend, we find in 10 studies (comprising uncertain events such as weather, climate change, sex, sports, and wine) that upward changes to event-probability (e.g., increasing from 20% to 30%) cause events to feel less remote than downward changes (e.g., decreasing from 40% to 30%), and subsequently change people's behavior regarding those events despite the revised event-probabilities being the same. Our research sheds light on how revising the probabilities for future events changes how people manage those uncertain events. (PsycINFO Database Record PMID:27281350
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.
Risks and probabilities of breast cancer: short-term versus lifetime probabilities.
Bryant, H E; Brasher, P M
1994-01-01
OBJECTIVE: To calculate age-specific short-term and lifetime probabilities of breast cancer among a cohort of Canadian women. DESIGN: Double decrement life table. SETTING: Alberta. SUBJECTS: Women with first invasive breast cancers registered with the Alberta Cancer Registry between 1985 and 1987. MAIN OUTCOME MEASURES: Lifetime probability of breast cancer from birth and for women at various ages; short-term (up to 10 years) probability of breast cancer for women at various ages. RESULTS: The lifetime probability of breast cancer is 10.17% at birth and peaks at 10.34% at age 25 years, after which it decreases owing to a decline in the number of years over which breast cancer risk will be experienced. However, the probability of manifesting breast cancer in the next year increases steadily from the age of 30 onward, reaching 0.36% at 85 years. The probability of manifesting the disease within the next 10 years peaks at 2.97% at age 70 and decreases thereafter, again owing to declining probabilities of surviving the interval. CONCLUSIONS: Given that the incidence of breast cancer among Albertan women during the study period was similar to the national average, we conclude that currently more than 1 in 10 women in Canada can expect to have breast cancer at some point during their life. However, risk varies considerably over a woman's lifetime, with most risk concentrated after age 49. On the basis of the shorter-term age-specific risks that we present, the clinician can put breast cancer risk into perspective for younger women and heighten awareness among women aged 50 years or more. PMID:8287343
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.
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.
Risk Preferences, Probability Weighting, and Strategy Tradeoffs in Wildfire Management.
Hand, Michael S; Wibbenmeyer, Matthew J; Calkin, David E; Thompson, Matthew P
2015-10-01
Wildfires present a complex applied risk management environment, but relatively little attention has been paid to behavioral and cognitive responses to risk among public agency wildfire managers. This study investigates responses to risk, including probability weighting and risk aversion, in a wildfire management context using a survey-based experiment administered to federal wildfire managers. Respondents were presented with a multiattribute lottery-choice experiment where each lottery is defined by three outcome attributes: expenditures for fire suppression, damage to private property, and exposure of firefighters to the risk of aviation-related fatalities. Respondents choose one of two strategies, each of which includes "good" (low cost/low damage) and "bad" (high cost/high damage) outcomes that occur with varying probabilities. The choice task also incorporates an information framing experiment to test whether information about fatality risk to firefighters alters managers' responses to risk. Results suggest that managers exhibit risk aversion and nonlinear probability weighting, which can result in choices that do not minimize expected expenditures, property damage, or firefighter exposure. Information framing tends to result in choices that reduce the risk of aviation fatalities, but exacerbates nonlinear probability weighting. PMID:26269258
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
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.
Image-based camera motion estimation using prior probabilities
NASA Astrophysics Data System (ADS)
Sargent, Dusty; Park, Sun Young; Spofford, Inbar; Vosburgh, Kirby
2011-03-01
Image-based camera motion estimation from video or still images is a difficult problem in the field of computer vision. Many algorithms have been proposed for estimating intrinsic camera parameters, detecting and matching features between images, calculating extrinsic camera parameters based on those features, and optimizing the recovered parameters with nonlinear methods. These steps in the camera motion inference process all face challenges in practical applications: locating distinctive features can be difficult in many types of scenes given the limited capabilities of current feature detectors, camera motion inference can easily fail in the presence of noise and outliers in the matched features, and the error surfaces in optimization typically contain many suboptimal local minima. The problems faced by these techniques are compounded when they are applied to medical video captured by an endoscope, which presents further challenges such as non-rigid scenery and severe barrel distortion of the images. In this paper, we study these problems and propose the use of prior probabilities to stabilize camera motion estimation for the application of computing endoscope motion sequences in colonoscopy. Colonoscopy presents a special case for camera motion estimation in which it is possible to characterize typical motion sequences of the endoscope. As the endoscope is restricted to move within a roughly tube-shaped structure, forward/backward motion is expected, with only small amounts of rotation and horizontal movement. We formulate a probabilistic model of endoscope motion by maneuvering an endoscope and attached magnetic tracker through a synthetic colon model and fitting a distribution to the observed motion of the magnetic tracker. This model enables us to estimate the probability of the current endoscope motion given previously observed motion in the sequence. We add these prior probabilities into the camera motion calculation as an additional penalty term in RANSAC
Probabilities and statistics for backscatter estimates obtained by a scatterometer
NASA Technical Reports Server (NTRS)
Pierson, Willard J., Jr.
1989-01-01
Methods for the recovery of winds near the surface of the ocean from measurements of the normalized radar backscattering cross section must recognize and make use of the statistics (i.e., the sampling variability) of the backscatter measurements. Radar backscatter values from a scatterometer are random variables with expected values given by a model. A model relates backscatter to properties of the waves on the ocean, which are in turn generated by the winds in the atmospheric marine boundary layer. The effective wind speed and direction at a known height for a neutrally stratified atmosphere are the values to be recovered from the model. The probability density function for the backscatter values is a normal probability distribution with the notable feature that the variance is a known function of the expected value. The sources of signal variability, the effects of this variability on the wind speed estimation, and criteria for the acceptance or rejection of models are discussed. A modified maximum likelihood method for estimating wind vectors is described. Ways to make corrections for the kinds of errors found for the Seasat SASS model function are described, and applications to a new scatterometer are given.
Failure probability estimate of Type 304 stainless steel piping
Daugherty, W L; Awadalla, N G; Sindelar, R L; Mehta, H S; Ranganath, S; General Electric Co., San Jose, CA )
1989-01-01
The primary source of in-service degradation of the SRS production reactor process water piping is intergranular stress corrosion cracking (IGSCC). IGSCC has occurred in a limited number of weld heat affected zones, areas known to be susceptible to IGSCC. A model has been developed to combine crack growth rates, crack size distributions, in-service examination reliability estimates and other considerations to estimate the pipe large-break frequency. This frequency estimates the probability that an IGSCC crack will initiate, escape detection by ultrasonic (UT) examination, and grow to instability prior to extending through-wall and being detected by the sensitive leak detection system. These four factors estimate the occurrence of several conditions that must coexist in order for a crack to lead to a large break of the process piping. When evaluated for the SRS production reactors, they produce an extremely low break frequency. The objective of this paper is to present the assumptions, methodology, results and conclusion of a probabilistic evaluation for the direct failure of the primary coolant piping resulting from normal operation and seismic loads. This evaluation was performed to support the ongoing PRA effort and to complement deterministic analyses addressing the credibility of a double-ended guillotine break. 5 refs., 2 figs.
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. PMID:26111548
Gray, David R
2010-12-01
As global trade increases so too does the probability of introduction of alien species to new locations. Estimating the probability of an alien species introduction and establishment following introduction is a necessary step in risk estimation (probability of an event times the consequences, in the currency of choice, of the event should it occur); risk estimation is a valuable tool for reducing the risk of biological invasion with limited resources. The Asian gypsy moth, Lymantria dispar (L.), is a pest species whose consequence of introduction and establishment in North America and New Zealand warrants over US$2 million per year in surveillance expenditure. This work describes the development of a two-dimensional phenology model (GLS-2d) that simulates insect development from source to destination and estimates: (1) the probability of introduction from the proportion of the source population that would achieve the next developmental stage at the destination and (2) the probability of establishment from the proportion of the introduced population that survives until a stable life cycle is reached at the destination. The effect of shipping schedule on the probabilities of introduction and establishment was examined by varying the departure date from 1 January to 25 December by weekly increments. The effect of port efficiency was examined by varying the length of time that invasion vectors (shipping containers and ship) were available for infection. The application of GLS-2d is demonstrated using three common marine trade routes (to Auckland, New Zealand, from Kobe, Japan, and to Vancouver, Canada, from Kobe and from Vladivostok, Russia). PMID:21265459
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
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…
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
Development of an integrated system for estimating human error probabilities
Auflick, J.L.; Hahn, H.A.; Morzinski, J.A.
1998-12-01
This is the final report of a three-year, Laboratory Directed Research and Development (LDRD) project at the Los Alamos National Laboratory (LANL). This project had as its main objective the development of a Human Reliability Analysis (HRA), knowledge-based expert system that would provide probabilistic estimates for potential human errors within various risk assessments, safety analysis reports, and hazard assessments. HRA identifies where human errors are most likely, estimates the error rate for individual tasks, and highlights the most beneficial areas for system improvements. This project accomplished three major tasks. First, several prominent HRA techniques and associated databases were collected and translated into an electronic format. Next, the project started a knowledge engineering phase where the expertise, i.e., the procedural rules and data, were extracted from those techniques and compiled into various modules. Finally, these modules, rules, and data were combined into a nearly complete HRA expert system.
Reinforcing flood-risk estimation.
Reed, Duncan W
2002-07-15
Flood-frequency estimation is inherently uncertain. The practitioner applies a combination of gauged data, scientific method and hydrological judgement to derive a flood-frequency curve for a particular site. The resulting estimate can be thought fully satisfactory only if it is broadly consistent with all that is reliably known about the flood-frequency behaviour of the river. The paper takes as its main theme the search for information to strengthen a flood-risk estimate made from peak flows alone. Extra information comes in many forms, including documentary and monumental records of historical floods, and palaeological markers. Meteorological information is also useful, although rainfall rarity is difficult to assess objectively and can be a notoriously unreliable indicator of flood rarity. On highly permeable catchments, groundwater levels present additional data. Other types of information are relevant to judging hydrological similarity when the flood-frequency estimate derives from data pooled across several catchments. After highlighting information sources, the paper explores a second theme: that of consistency in flood-risk estimates. Following publication of the Flood estimation handbook, studies of flood risk are now using digital catchment data. Automated calculation methods allow estimates by standard methods to be mapped basin-wide, revealing anomalies at special sites such as river confluences. Such mapping presents collateral information of a new character. Can this be used to achieve flood-risk estimates that are coherent throughout a river basin? PMID:12804255
NASA Astrophysics Data System (ADS)
Mandal, S.; Choudhury, B. U.
2015-07-01
Sagar Island, setting on the continental shelf of Bay of Bengal, is one of the most vulnerable deltas to the occurrence of extreme rainfall-driven climatic hazards. Information on probability of occurrence of maximum daily rainfall will be useful in devising risk management for sustaining rainfed agrarian economy vis-a-vis food and livelihood security. Using six probability distribution models and long-term (1982-2010) daily rainfall data, we studied the probability of occurrence of annual, seasonal and monthly maximum daily rainfall (MDR) in the island. To select the best fit distribution models for annual, seasonal and monthly time series based on maximum rank with minimum value of test statistics, three statistical goodness of fit tests, viz. Kolmogorove-Smirnov test (K-S), Anderson Darling test ( A 2 ) and Chi-Square test ( X 2) were employed. The fourth probability distribution was identified from the highest overall score obtained from the three goodness of fit tests. Results revealed that normal probability distribution was best fitted for annual, post-monsoon and summer seasons MDR, while Lognormal, Weibull and Pearson 5 were best fitted for pre-monsoon, monsoon and winter seasons, respectively. The estimated annual MDR were 50, 69, 86, 106 and 114 mm for return periods of 2, 5, 10, 20 and 25 years, respectively. The probability of getting an annual MDR of >50, >100, >150, >200 and >250 mm were estimated as 99, 85, 40, 12 and 03 % level of exceedance, respectively. The monsoon, summer and winter seasons exhibited comparatively higher probabilities (78 to 85 %) for MDR of >100 mm and moderate probabilities (37 to 46 %) for >150 mm. For different recurrence intervals, the percent probability of MDR varied widely across intra- and inter-annual periods. In the island, rainfall anomaly can pose a climatic threat to the sustainability of agricultural production and thus needs adequate adaptation and mitigation measures.
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
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.
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.
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
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 Risk: Stereotype Amplification and the Perceived Risk of Criminal Victimization
ERIC Educational Resources Information Center
Quillian, Lincoln; Pager, Devah
2010-01-01
This paper considers the process by which individuals estimate the risk of adverse events, with particular attention to the social context in which risk estimates are formed. We compare subjective probability estimates of crime victimization to actual victimization experiences among respondents from the 1994 to 2002 waves of the Survey of Economic…
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. PMID:22576139
Estimating the Probability of Elevated Nitrate Concentrations in Ground Water in Washington State
Frans, Lonna M.
2008-01-01
Logistic regression was used to relate anthropogenic (manmade) and natural variables to the occurrence of elevated nitrate concentrations in ground water in Washington State. Variables that were analyzed included well depth, ground-water recharge rate, precipitation, population density, fertilizer application amounts, soil characteristics, hydrogeomorphic regions, and land-use types. Two models were developed: one with and one without the hydrogeomorphic regions variable. The variables in both models that best explained the occurrence of elevated nitrate concentrations (defined as concentrations of nitrite plus nitrate as nitrogen greater than 2 milligrams per liter) were the percentage of agricultural land use in a 4-kilometer radius of a well, population density, precipitation, soil drainage class, and well depth. Based on the relations between these variables and measured nitrate concentrations, logistic regression models were developed to estimate the probability of nitrate concentrations in ground water exceeding 2 milligrams per liter. Maps of Washington State were produced that illustrate these estimated probabilities for wells drilled to 145 feet below land surface (median well depth) and the estimated depth to which wells would need to be drilled to have a 90-percent probability of drawing water with a nitrate concentration less than 2 milligrams per liter. Maps showing the estimated probability of elevated nitrate concentrations indicated that the agricultural regions are most at risk followed by urban areas. The estimated depths to which wells would need to be drilled to have a 90-percent probability of obtaining water with nitrate concentrations less than 2 milligrams per liter exceeded 1,000 feet in the agricultural regions; whereas, wells in urban areas generally would need to be drilled to depths in excess of 400 feet.
The conditional risk probability-based seawall height design method
NASA Astrophysics Data System (ADS)
Yang, Xing; Hu, Xiaodong; Li, Zhiqing
2015-11-01
The determination of the required seawall height is usually based on the combination of wind speed (or wave height) and still water level according to a specified return period, e.g., 50-year return period wind speed and 50-year return period still water level. In reality, the two variables are be partially correlated. This may be lead to over-design (costs) of seawall structures. The above-mentioned return period for the design of a seawall depends on economy, society and natural environment in the region. This means a specified risk level of overtopping or damage of a seawall structure is usually allowed. The aim of this paper is to present a conditional risk probability-based seawall height design method which incorporates the correlation of the two variables. For purposes of demonstration, the wind speeds and water levels collected from Jiangsu of China are analyzed. The results show this method can improve seawall height design accuracy.
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. PMID:26070026
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.
Development of partial failure analysis method in probability risk assessments
Ni, T.; Modarres, M.
1996-12-01
This paper presents a new approach to evaluate the partial failure effect on current Probability Risk Assessments (PRAs). An integrated methodology of the thermal-hydraulic analysis and fuzzy logic simulation using the Dynamic Master Logic Diagram (DMLD) was developed. The thermal-hydraulic analysis used in this approach is to identify partial operation effect of any PRA system function in a plant model. The DMLD is used to simulate the system performance of the partial failure effect and inspect all minimal cut sets of system functions. This methodology can be applied in the context of a full scope PRA to reduce core damage frequency. An example of this application of the approach is presented. The partial failure data used in the example is from a survey study of partial failure effects from the Nuclear Plant Reliability Data System (NPRDS).
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.
Not Available
1989-08-01
This report presents a Monte Carlo Simulation analysis of the fate and transport of Contaminants in groundwater at the Lawrence Livermore National Laboratory Livermore Site. The result of this analysis are the cumulative distribution function (CDF) of the maximum 70-year average and peak concentrations of the four chemicals of concern (TCE, PCE, chloroform, and other VOCs'') at the near-field and three far-field wells. These concentration CDFs can be used to estimate the probability of occurrence of the concentrations previously predicted using the deterministic model, and to conduct an enhanced exposure and risk assessment for the Remedial Investigation and Feasibility Study (RI/FS). This report provides a description of the deterministic fate and transport model (PLUME) which was linked to the Monte Carlo Shell to estimate the CDF of the receptor-well chemical concentrations. 6 refs., 21 figs., 12 tabs.
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
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
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).
Estimating the risk of Amazonian forest dieback.
Rammig, Anja; Jupp, Tim; Thonicke, Kirsten; Tietjen, Britta; Heinke, Jens; Ostberg, Sebastian; Lucht, Wolfgang; Cramer, Wolfgang; Cox, Peter
2010-08-01
*Climate change will very likely affect most forests in Amazonia during the course of the 21st century, but the direction and intensity of the change are uncertain, in part because of differences in rainfall projections. In order to constrain this uncertainty, we estimate the probability for biomass change in Amazonia on the basis of rainfall projections that are weighted by climate model performance for current conditions. *We estimate the risk of forest dieback by using weighted rainfall projections from 24 general circulation models (GCMs) to create probability density functions (PDFs) for future forest biomass changes simulated by a dynamic vegetation model (LPJmL). *Our probabilistic assessment of biomass change suggests a likely shift towards increasing biomass compared with nonweighted results. Biomass estimates range between a gain of 6.2 and a loss of 2.7 kg carbon m(-2) for the Amazon region, depending on the strength of CO(2) fertilization. *The uncertainty associated with the long-term effect of CO(2) is much larger than that associated with precipitation change. This underlines the importance of reducing uncertainties in the direct effects of CO(2) on tropical ecosystems. PMID:20553387
The variance and two estimators of variance of the Horvitz-Thompson estimator were studied under randomized, variable probability systematic sampling. hree bivariate distributions, representing the populations, were investigated empirically, with each distribution studied for thr...
Robust location and spread measures for nonparametric probability density function estimation.
López-Rubio, Ezequiel
2009-10-01
Robustness against outliers is a desirable property of any unsupervised learning scheme. In particular, probability density estimators benefit from incorporating this feature. A possible strategy to achieve this goal is to substitute the sample mean and the sample covariance matrix by more robust location and spread estimators. Here we use the L1-median to develop a nonparametric probability density function (PDF) estimator. We prove its most relevant properties, and we show its performance in density estimation and classification applications. PMID:19885963
Student Estimates of Probability and Uncertainty in Statistical Physics
NASA Astrophysics Data System (ADS)
Mountcastle, Donald B.; Bucy, B. R.; Thompson, J. R.
2006-12-01
Equilibrium properties of macroscopic (large N) systems are highly predictable as N approaches and exceeds Avogadro’s number. Theories of statistical physics depend on these results. Typical pedagogical devices used in statistical physics textbooks to introduce entropy (S) and multiplicity [S = k ln(w), where w is the system multiplicity] include flipping coins and/or other equivalent binary events, repeated n times. Prior to instruction, our students usually give reasonable answers about the probabilities, but not the uncertainties of the predicted outcomes of such events. However, they reliably predict that the uncertainty in a measured quantity (e.g., the amount of rainfall) decreases as the number of measurements increases. Typical textbook presentations presume that students will either have or develop the insight that the relative uncertainty of binary outcomes will similarly decrease as the number of events increases. That is at odds with our findings among students in two successive statistical mechanics classes. Many of our students had previously completed mathematics courses in statistics, as well as a physics laboratory course that included analysis of statistical properties of distributions of dart scores as the number (n) of throws (one-dimensional target) increased. There was a wide divergence of predictions about how the standard deviation of the distribution of dart scores should change, or not, as n increases. We find that student predictions about statistics of coin flips, dart scores, and rainfall amounts as functions of n are inconsistent at best. Supported in part by NSF Grant #PHY-0406764.
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 Earthquake-Induced Landslides
NASA Astrophysics Data System (ADS)
McRae, M. E.; Christman, M. C.; Soller, D. R.; Sutter, J. F.
2001-12-01
The development of a regionally applicable, predictive model for earthquake-triggered landslides is needed to improve mitigation decisions at the community level. The distribution of landslides triggered by the 1994 Northridge earthquake in the Oat Mountain and Simi Valley quadrangles of southern California provided an inventory of failures against which to evaluate the significance of a variety of physical variables in probabilistic models of static slope stability. Through a cooperative project, the California Division of Mines and Geology provided 10-meter resolution data on elevation, slope angle, coincidence of bedding plane and topographic slope, distribution of pre-Northridge landslides, internal friction angle and cohesive strength of individual geologic units. Hydrologic factors were not evaluated since failures in the study area were dominated by shallow, disrupted landslides in dry materials. Previous studies indicate that 10-meter digital elevation data is required to properly characterize the short, steep slopes on which many earthquake-induced landslides occur. However, to explore the robustness of the model at different spatial resolutions, models were developed at the 10, 50, and 100-meter resolution using classification and regression tree (CART) analysis and logistic regression techniques. Multiple resampling algorithms were tested for each variable in order to observe how resampling affects the statistical properties of each grid, and how relationships between variables within the model change with increasing resolution. Various transformations of the independent variables were used to see which had the strongest relationship with the probability of failure. These transformations were based on deterministic relationships in the factor of safety equation. Preliminary results were similar for all spatial scales. Topographic variables dominate the predictive capability of the models. The distribution of prior landslides and the coincidence of slope
A simulation model for estimating probabilities of defects in welds
Chapman, O.J.V.; Khaleel, M.A.; Simonen, F.A.
1996-12-01
In recent work for the US Nuclear Regulatory Commission in collaboration with Battelle Pacific Northwest National Laboratory, Rolls-Royce and Associates, Ltd., has adapted an existing model for piping welds to address welds in reactor pressure vessels. This paper describes the flaw estimation methodology as it applies to flaws in reactor pressure vessel welds (but not flaws in base metal or flaws associated with the cladding process). Details of the associated computer software (RR-PRODIGAL) are provided. The approach uses expert elicitation and mathematical modeling to simulate the steps in manufacturing a weld and the errors that lead to different types of weld defects. The defects that may initiate in weld beads include center cracks, lack of fusion, slag, pores with tails, and cracks in heat affected zones. Various welding processes are addressed including submerged metal arc welding. The model simulates the effects of both radiographic and dye penetrant surface inspections. Output from the simulation gives occurrence frequencies for defects as a function of both flaw size and flaw location (surface connected and buried flaws). Numerical results are presented to show the effects of submerged metal arc versus manual metal arc weld processes.
Estimating Risk: Stereotype Amplification and the Perceived Risk of Criminal Victimization.
Quillian, Lincoln; Pager, Devah
2010-03-01
This paper considers the process by which individuals estimate the risk of adverse events, with particular attention to the social context in which risk estimates are formed. We compare subjective probability estimates of crime victimization to actual victimization experiences among respondents from the 1994 to 2002 waves of the Survey of Economic Expectations (Dominitz and Manski 2002). Using zip code identifiers, we then match these survey data to local area characteristics from the census. The results show that: (1) the risk of criminal victimization is significantly overestimated relative to actual rates of victimization or other negative events; (2) neighborhood racial composition is strongly associated with perceived risk of victimization, whereas actual victimization risk is driven by nonracial neighborhood characteristics; and (3) white respondents appear more strongly affected by racial composition than nonwhites in forming their estimates of risk. We argue these results support a model of stereotype amplification in the formation of risk estimates. Implications for persistent racial inequality are considered. PMID:20686631
Estimating Risk: Stereotype Amplification and the Perceived Risk of Criminal Victimization
QUILLIAN, LINCOLN; PAGER, DEVAH
2010-01-01
This paper considers the process by which individuals estimate the risk of adverse events, with particular attention to the social context in which risk estimates are formed. We compare subjective probability estimates of crime victimization to actual victimization experiences among respondents from the 1994 to 2002 waves of the Survey of Economic Expectations (Dominitz and Manski 2002). Using zip code identifiers, we then match these survey data to local area characteristics from the census. The results show that: (1) the risk of criminal victimization is significantly overestimated relative to actual rates of victimization or other negative events; (2) neighborhood racial composition is strongly associated with perceived risk of victimization, whereas actual victimization risk is driven by nonracial neighborhood characteristics; and (3) white respondents appear more strongly affected by racial composition than nonwhites in forming their estimates of risk. We argue these results support a model of stereotype amplification in the formation of risk estimates. Implications for persistent racial inequality are considered. PMID:20686631
Extreme Earthquake Risk Estimation by Hybrid Modeling
NASA Astrophysics Data System (ADS)
Chavez, M.; Cabrera, E.; Ashworth, M.; Garcia, S.; Emerson, D.; Perea, N.; Salazar, A.; Moulinec, C.
2012-12-01
The estimation of the hazard and the economical consequences i.e. the risk associated to the occurrence of extreme magnitude earthquakes in the neighborhood of urban or lifeline infrastructure, such as the 11 March 2011 Mw 9, Tohoku, Japan, represents a complex challenge as it involves the propagation of seismic waves in large volumes of the earth crust, from unusually large seismic source ruptures up to the infrastructure location. The large number of casualties and huge economic losses observed for those earthquakes, some of which have a frequency of occurrence of hundreds or thousands of years, calls for the development of new paradigms and methodologies in order to generate better estimates, both of the seismic hazard, as well as of its consequences, and if possible, to estimate the probability distributions of their ground intensities and of their economical impacts (direct and indirect losses), this in order to implement technological and economical policies to mitigate and reduce, as much as possible, the mentioned consequences. Herewith, we propose a hybrid modeling which uses 3D seismic wave propagation (3DWP) and neural network (NN) modeling in order to estimate the seismic risk of extreme earthquakes. The 3DWP modeling is achieved by using a 3D finite difference code run in the ~100 thousands cores Blue Gene Q supercomputer of the STFC Daresbury Laboratory of UK, combined with empirical Green function (EGF) techniques and NN algorithms. In particular the 3DWP is used to generate broadband samples of the 3D wave propagation of extreme earthquakes (plausible) scenarios corresponding to synthetic seismic sources and to enlarge those samples by using feed-forward NN. We present the results of the validation of the proposed hybrid modeling for Mw 8 subduction events, and show examples of its application for the estimation of the hazard and the economical consequences, for extreme Mw 8.5 subduction earthquake scenarios with seismic sources in the Mexican
Climate-informed flood risk estimation
NASA Astrophysics Data System (ADS)
Troy, T.; Devineni, N.; Lima, C.; Lall, U.
2013-12-01
Currently, flood risk assessments are typically tied to a peak flow event that has an associated return period and inundation extent. This method is convenient: based on a historical record of annual maximum flows, a return period can be calculated with some assumptions about the probability distribution and stationarity. It is also problematic in its stationarity assumption, reliance on relatively short records, and treating flooding as a random event disconnected from large-scale climate processes. Recognizing these limitations, we have developed a new approach to flood risk assessment that connects climate variability, precipitation dynamics, and flood modeling to estimate the likelihood of flooding. To provide more robust, long time series of precipitation, we used stochastic weather generator models to simulate the rainfall fields. The method uses a k-nearest neighbor resampling algorithm in conjunction with a non-parametric empirical copulas based simulation strategy to reproduce the temporal and spatial dynamics, respectively. Climate patterns inform the likelihood of heavy rainfall in the model. For example, ENSO affects the likelihood of wet or dry years in Australia, and this is incorporated in the model. The stochastic simulations are then used to drive a cascade of models to predict flood inundation. Runoff is generated by the Variable Infiltration Capacity (VIC) model, fed into a full kinematic wave routing model at high resolution, and the kinematic wave is used as a boundary condition to predict flood inundation using a coupled storage cell model. Combining the strengths of a stochastic model for rainfall and a physical model for flood prediction allows us to overcome the limitations of traditional flood risk assessment and provide robust estimates of flood risk.
Statistical Surrogate Models for Estimating Probability of High-Consequence Climate Change
NASA Astrophysics Data System (ADS)
Field, R.; Constantine, P.; Boslough, M.
2011-12-01
We have posed the climate change problem in a framework similar to that used in safety engineering, by acknowledging that probabilistic risk assessments focused on low-probability, high-consequence climate events are perhaps more appropriate than studies focused simply on best estimates. To properly explore the tails of the distribution requires extensive sampling, which is not possible with existing coupled atmospheric models due to the high computational cost of each simulation. We have developed specialized statistical surrogate models (SSMs) that can be used to make predictions about the tails of the associated probability distributions. A SSM is different than a deterministic surrogate model in that it represents each climate variable of interest as a space/time random field, that is, a random variable for every fixed location in the atmosphere at all times. The SSM can be calibrated to available spatial and temporal data from existing climate databases, or to a collection of outputs from general circulation models. Because of its reduced size and complexity, the realization of a large number of independent model outputs from a SSM becomes computationally straightforward, so that quantifying the risk associated with low-probability, high-consequence climate events becomes feasible. A Bayesian framework was also developed to provide quantitative measures of confidence, via Bayesian credible intervals, to assess these risks. To illustrate the use of the SSM, we considered two collections of NCAR CCSM 3.0 output data. The first collection corresponds to average December surface temperature for years 1990-1999 based on a collection of 8 different model runs obtained from the Program for Climate Model Diagnosis and Intercomparison (PCMDI). We calibrated the surrogate model to the available model data and make various point predictions. We also analyzed average precipitation rate in June, July, and August over a 54-year period assuming a cyclic Y2K ocean model. We
An Illustration of Inverse Probability Weighting to Estimate Policy-Relevant Causal Effects.
Edwards, Jessie K; Cole, Stephen R; Lesko, Catherine R; Mathews, W Christopher; Moore, Richard D; Mugavero, Michael J; Westreich, Daniel
2016-08-15
Traditional epidemiologic approaches allow us to compare counterfactual outcomes under 2 exposure distributions, usually 100% exposed and 100% unexposed. However, to estimate the population health effect of a proposed intervention, one may wish to compare factual outcomes under the observed exposure distribution to counterfactual outcomes under the exposure distribution produced by an intervention. Here, we used inverse probability weights to compare the 5-year mortality risk under observed antiretroviral therapy treatment plans to the 5-year mortality risk that would had been observed under an intervention in which all patients initiated therapy immediately upon entry into care among patients positive for human immunodeficiency virus in the US Centers for AIDS Research Network of Integrated Clinical Systems multisite cohort study between 1998 and 2013. Therapy-naïve patients (n = 14,700) were followed from entry into care until death, loss to follow-up, or censoring at 5 years or on December 31, 2013. The 5-year cumulative incidence of mortality was 11.65% under observed treatment plans and 10.10% under the intervention, yielding a risk difference of -1.57% (95% confidence interval: -3.08, -0.06). Comparing outcomes under the intervention with outcomes under observed treatment plans provides meaningful information about the potential consequences of new US guidelines to treat all patients with human immunodeficiency virus regardless of CD4 cell count under actual clinical conditions. PMID:27469514
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. PMID:24918785
Estimating site occupancy and species detection probability parameters for terrestrial salamanders
Bailey, L.L.; Simons, T.R.; Pollock, K.H.
2004-01-01
Recent, worldwide amphibian declines have highlighted a need for more extensive and rigorous monitoring programs to document species occurrence and detect population change. Abundance estimation methods, such as mark-recapture, are often expensive and impractical for large-scale or long-term amphibian monitoring. We apply a new method to estimate proportion of area occupied using detection/nondetection data from a terrestrial salamander system in Great Smoky Mountains National Park. Estimated species-specific detection probabilities were all <1 and varied among seven species and four sampling methods. Time (i.e., sampling occasion) and four large-scale habitat characteristics (previous disturbance history, vegetation type, elevation, and stream presence) were important covariates in estimates of both proportion of area occupied and detection probability. All sampling methods were consistent in their ability to identify important covariates for each salamander species. We believe proportion of area occupied represents a useful state variable for large-scale monitoring programs. However, our results emphasize the importance of estimating detection and occupancy probabilities rather than using an unadjusted proportion of sites where species are observed where actual occupancy probabilities are confounded with detection probabilities. Estimated detection probabilities accommodate variations in sampling effort; thus comparisons of occupancy probabilities are possible among studies with different sampling protocols.
ERIC Educational Resources Information Center
Acredolo, Curt; And Others
1989-01-01
Two studies assessed 90 elementary school students' attention to the total number of alternative and target outcomes when making probability estimates. All age groups attended to variations in the denominator and numerator and the interaction between these variables. (RJC)
How to estimate the Value at Risk under incomplete information
NASA Astrophysics Data System (ADS)
de Schepper, Ann; Heijnen, Bart
2010-03-01
A key problem in financial and actuarial research, and particularly in the field of risk management, is the choice of models so as to avoid systematic biases in the measurement of risk. An alternative consists of relaxing the assumption that the probability distribution is completely known, leading to interval estimates instead of point estimates. In the present contribution, we show how this is possible for the Value at Risk, by fixing only a small number of parameters of the underlying probability distribution. We start by deriving bounds on tail probabilities, and we show how a conversion leads to bounds for the Value at Risk. It will turn out that with a maximum of three given parameters, the best estimates are always realized in the case of a unimodal random variable for which two moments and the mode are given. It will also be shown that a lognormal model results in estimates for the Value at Risk that are much closer to the upper bound than to the lower bound.
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.
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
Methodology for estimating extreme winds for probabilistic risk assessments
Ramsdell, J.V.; Elliott, D.L.; Holladay, C.G.; Hubbe, J.M.
1986-10-01
The US Nuclear Reguulatory Commission (NRC) assesses the risks associated with nuclear faciliies using techniques that fall under a generic name of Probabilistic Risk Assessment. In these assessments, potential accident sequences are traced from initiating event to final outcome. At each step of the sequence, a probability of occurrence is assigned to each available alternative. Ultimately, the probability of occurrence of each possible outcome is determined from the probabilities assigned to the initiating events and the alternative paths. Extreme winds are considered in these sequences. As a result, it is necessary to estimate extreme wind probabilities as low as 10/sup -7/yr/sup -1/. When the NRC staff is called on to provide extreme wind estimates, the staff is likely to be subjected to external time and funding constraints. These constraints dictate that the estimates be based on readily available wind data. In general, readily available data will be limited to the data provided by the facility applicant or licensee and the data archived at the National Climatic Data Center in Asheville, North Carolina. This report describes readily available data that can be used in estimating extreme wind probabilities, procedures of screening the data to eliminate erroneous values and for adjusting data to compensate for differences in data collection methods, and statistical methods for making extreme wind estimates. Supporting technical details are presented in several appendices. Estimation of extreme wind probabilities at a given location involves many subjective decisions. The procedures described do not eliminate all of the subjectivity, but they do increase the reproducibility of the analysis. They provide consistent methods for determining probabilities given a set of subjective decisions. By following these procedures, subjective decisions can be identified and documented.
Estimating functions of probability distributions from a finite set of samples
Wolpert, D.H.; Wolf, D.R. |
1995-12-01
This paper addresses the problem of estimating a function of a probability distribution from a finite set of samples of that distribution. A Bayesian analysis of this problem is presented, the optimal properties of the Bayes estimators are discussed, and as an example of the formalism, closed form expressions for the Bayes estimators for the moments of the Shannon entropy function are derived. Then numerical results are presented that compare the Bayes estimator to the frequency-counts estimator for the Shannon entropy. We also present the closed form estimators, all derived elsewhere, for the mutual information, {chi}{sup 2} covariance, and some other statistics. (c) 1995 The American Physical Society
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.
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
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.
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).
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
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
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.
Estimating probabilities of reservoir storage for the upper Delaware River basin
Hirsch, Robert M.
1981-01-01
A technique for estimating conditional probabilities of reservoir system storage is described and applied to the upper Delaware River Basin. The results indicate that there is a 73 percent probability that the three major New York City reservoirs (Pepacton, Cannonsville, and Neversink) would be full by June 1, 1981, and only a 9 percent probability that storage would return to the ' drought warning ' sector of the operations curve sometime in the next year. In contrast, if restrictions are lifted and there is an immediate return to normal operating policies, the probability of the reservoir system being full by June 1 is 37 percent and the probability that storage would return to the ' drought warning ' sector in the next year is 30 percent. (USGS)
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.
Estimate of the probability of a lightning strike to the Galileo probe
NASA Astrophysics Data System (ADS)
Borucki, W. J.
1985-04-01
Lightning strikes to aerospace vehicles occur mainly in or near clouds. As the Galileo entry probe will pass most of its operational life in the clouds of Jupiter, which is known to have lightning activity, the present study is concerned with the risk of a lightning strike to the probe. A strike to the probe could cause physical damage to the structure and/or damage to the electronic equipment aboard the probe. It is thought to be possible, for instance, that the instrument failures which occurred on all four Pioneer Venus entry probes at an altitude of 12 km were due to an external electric discharge. The probability of a lightning strike to the Galileo probe is evaluated. It is found that the estimate of a strike to the probe is only 0.001, which is about the same as the expected failure rate due to other design factors. In the case of entry probes to cloud-covered planets, a consideration of measures for protecting the vehicle and its payload from lightning appears to be appropriate.
Estimate of the probability of a lightning strike to the Galileo probe
NASA Technical Reports Server (NTRS)
Borucki, W. J.
1985-01-01
Lightning strikes to aerospace vehicles occur mainly in or near clouds. As the Galileo entry probe will pass most of its operational life in the clouds of Jupiter, which is known to have lightning activity, the present study is concerned with the risk of a lightning strike to the probe. A strike to the probe could cause physical damage to the structure and/or damage to the electronic equipment aboard the probe. It is thought to be possible, for instance, that the instrument failures which occurred on all four Pioneer Venus entry probes at an altitude of 12 km were due to an external electric discharge. The probability of a lightning strike to the Galileo probe is evaluated. It is found that the estimate of a strike to the probe is only 0.001, which is about the same as the expected failure rate due to other design factors. In the case of entry probes to cloud-covered planets, a consideration of measures for protecting the vehicle and its payload from lightning appears to be appropriate.
Estimation of Hail Risk in the UK and Europe
NASA Astrophysics Data System (ADS)
Robinson, Eric; Parker, Melanie; Higgs, Stephanie
2016-04-01
Observations of hail events in Europe, and the UK especially, are relatively limited. In order to determine hail risk it is therefore necessary to use information other than relying purely on the historical record. One such methodology is to leverage reanalysis data, in this case ERA-Interim, along with a numerical model (WRF) to recreate the past state of the atmosphere. Relevant atmospheric properties can be extracted and used in a regression model to determine hail probability for each day contained within the reanalyses. The results presented here show the results of using a regression model based on convective available potential energy, deep level shear and weather type. Combined these parameters represent the probability of severe thunderstorm, and in turn hail, activity. Once the probability of hail occurring on each day is determined this can be used as the basis of a stochastic catalogue which can be used in the estimation of hail risk.
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.
Jordan, Preston D.; Oldenburg, Curtis M.; Nicot, Jean-Philippe
2008-11-01
Leakage of CO{sub 2} out of the designated storage region via faults is a widely recognized concern for geologic carbon sequestration. The probability of such leakage can be separated into the probability of a plume encountering a fault and the probability of flow along such a fault. In the absence of deterministic fault location information, the first probability can be calculated from regional fault population statistics and modeling of the plume shape and size. In this study, fault statistical parameters were measured or estimated for WESTCARB's Phase III pilot test injection in the San Joaquin Valley, California. Combining CO{sub 2} plume model predictions with estimated fault characteristics resulted in a 3% probability that the CO{sub 2} plume will encounter a fault fully offsetting the 180 m (590 ft) thick seal. The probability of leakage is lower, likely much lower, as faults with this offset are probably low-permeability features in this area.
Estimating the posterior probability that genome-wide association findings are true or false
Bukszár, József; McClay, Joseph L.; van den Oord, Edwin J. C. G.
2009-01-01
Motivation: A limitation of current methods used to declare significance in genome-wide association studies (GWAS) is that they do not provide clear information about the probability that GWAS findings are true of false. This lack of information increases the chance of false discoveries and may result in real effects being missed. Results: We propose a method to estimate the posterior probability that a marker has (no) effect given its test statistic value, also called the local false discovery rate (FDR), in the GWAS. A critical step involves the estimation the parameters of the distribution of the true alternative tests. For this, we derived and implemented the real maximum likelihood function, which turned out to provide us with significantly more accurate estimates than the widely used mixture model likelihood. Actual GWAS data are used to illustrate properties of the posterior probability estimates empirically. In addition to evaluating individual markers, a variety of applications are conceivable. For instance, posterior probability estimates can be used to control the FDR more precisely than Benjamini–Hochberg procedure. Availability: The codes are freely downloadable from the web site http://www.people.vcu.edu/∼jbukszar. Contact: jbukszar@vcu.edu Supplementary information: Supplementary data are available at Bioinformatics online. PMID:19420056
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
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…
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
Probabilities of arsenic occurrence in groundwater from bedrock aquifers at concentrations of 1, 5, and 10 micrograms per liter (µg/L) were estimated during 2011 using multivariate logistic regression. These estimates were developed for use by the New Hampshire Environmental Public Health Tracking Program. About 39 percent of New Hampshire bedrock groundwater was identified as having at least a 50 percent chance of containing an arsenic concentration greater than or equal to 1 µg/L. This compares to about 7 percent of New Hampshire bedrock groundwater having at least a 50 percent chance of containing an arsenic concentration equaling or exceeding 5 µg/L and about 5 percent of the State having at least a 50 percent chance for its bedrock groundwater to contain concentrations at or above 10 µg/L. The southeastern counties of Merrimack, Strafford, Hillsborough, and Rockingham have the greatest potential for having arsenic concentrations above 5 and 10 µg/L in bedrock groundwater. Significant predictors of arsenic in groundwater from bedrock aquifers for all three thresholds analyzed included geologic, geochemical, land use, hydrologic, topographic, and demographic factors. Among the three thresholds evaluated, there were some differences in explanatory variables, but many variables were the same. More than 250 individual predictor variables were assembled for this study and tested as potential predictor variables for the models. More than 1,700 individual measurements of arsenic concentration from a combination of public and private water-supply wells served as the dependent (or predicted) variable in the models. 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
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
Dynamic cost risk estimation and budget misspecification
NASA Technical Reports Server (NTRS)
Ebbeler, D. H.; Fox, G.; Habib-Agahi, H.
2003-01-01
Cost risk for new technology development is estimated by explicit stochastic processes. Monte Carlo simulation is used to propagate technology development activity budget changes during the technology development cycle.
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
Estimating probability densities from short samples: A parametric maximum likelihood approach
NASA Astrophysics Data System (ADS)
Dudok de Wit, T.; Floriani, E.
1998-10-01
A parametric method similar to autoregressive spectral estimators is proposed to determine the probability density function (PDF) of a random set. The method proceeds by maximizing the likelihood of the PDF, yielding estimates that perform equally well in the tails as in the bulk of the distribution. It is therefore well suited for the analysis of short sets drawn from smooth PDF's and stands out by the simplicity of its computational scheme. Its advantages and limitations are discussed.
Juang, K.W.; Lee, D.Y.
1998-09-01
The probability of incorrectly delineating hazardous areas in a contaminated site is very important for decision-makers because it indicates the magnitude of confidence that decision-makers have in determining areas in need of remediation. In this study, simple indicator kriging (SIK) was used to estimate the probability of incorrectly delineating hazardous areas in a heavy metal-contaminated site, which is located at Taoyuan, Taiwan, and is about 10 ha in area. In the procedure, the values 0 and 1 were assigned to be the stationary means of the indicator codes in the SIK model to represent two hypotheses, hazardous and safe, respectively. The spatial distribution of the conditional probability of heavy metal concentrations lower than a threshold, given each hypothesis, was estimated using SIK. Then, the probabilities of false positives ({alpha}) (i.e., the probability of declaring a location hazardous when it is not) and false negatives ({beta}) (i.e., the probability of declaring a location safe when it is not) in delineating hazardous areas for the heavy metal-contaminated site could be obtained. The spatial distribution of the probabilities of false positives and false negatives could help in delineating hazardous areas based on a tolerable probability level of incorrect delineation. In addition, delineation complicated by the cost of remediation, hazards in the environment, and hazards to human health could be made based on the minimum values of {alpha} and {beta}. The results suggest that the proposed SIK procedure is useful for decision-makers who need to delineate hazardous areas in a heavy metal-contaminated site.
Uranium mill tailings and risk estimation
Marks, S.
1984-04-01
Work done in estimating projected health effects for persons exposed to mill tailings at vicinity properties is described. The effect of the reassessment of exposures at Hiroshima and Nagasaki on the risk estimates for gamma radiation is discussed. A presentation of current results in the epidemiological study of Hanford workers is included. 2 references. (ACR)
O'Connell, A.F., Jr.; Talancy, N.W.; Bailey, L.L.; Sauer, J.R.; Cook, R.; Gilbert, A.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
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. PMID:21231945
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.
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. PMID:25109085
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.
Population-based absolute risk estimation with survey data.
Kovalchik, Stephanie A; Pfeiffer, Ruth M
2014-04-01
Absolute risk is the probability that a cause-specific event occurs in a given time interval in the presence of competing events. We present methods to estimate population-based absolute risk from a complex survey cohort that can accommodate multiple exposure-specific competing risks. The hazard function for each event type consists of an individualized relative risk multiplied by a baseline hazard function, which is modeled nonparametrically or parametrically with a piecewise exponential model. An influence method is used to derive a Taylor-linearized variance estimate for the absolute risk estimates. We introduce novel measures of the cause-specific influences that can guide modeling choices for the competing event components of the model. To illustrate our methodology, we build and validate cause-specific absolute risk models for cardiovascular and cancer deaths using data from the National Health and Nutrition Examination Survey. Our applications demonstrate the usefulness of survey-based risk prediction models for predicting health outcomes and quantifying the potential impact of disease prevention programs at the population level. PMID:23686614
Effects of prior detections on estimates of detection probability, abundance, and occupancy
Riddle, Jason D.; Mordecai, Rua S.; Pollock, Kenneth H.; Simons, Theodore R.
2010-01-01
Survey methods that account for detection probability often require repeated detections of individual birds or repeated visits to a site to conduct Counts or collect presence-absence data. Initial encounters with individual species or individuals of a species could influence detection probabilities for subsequent encounters. For example, observers may be more likely to redetect a species or individual once they are aware of the presence of that species or individual at a particular site. Not accounting for these effects could result in biased estimators of detection probability, abundance, and occupancy. We tested for effects of prior detections in three data sets that differed dramatically by species, geographic location, and method of counting birds. We found strong support (AIC weights from 83% to 100%) for models that allowed for the effects of prior detections. These models produced estimates of detection probability, abundance, and occupancy that differed substantially from those produced by models that ignored the effects of prior detections. We discuss the consequences of the effects of prior detections on estimation for several sampling methods and provide recommendations for avoiding these effects through survey design or by modeling them when they cannot be avoided.
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.
Hanayama, Nobutane; Sibuya, Masaaki
2016-08-01
In modern biology, theories of aging fall mainly into two groups: damage theories and programed theories. If programed theories are true, the probability that human beings live beyond a specific age will be zero. In contrast, if damage theories are true, such an age does not exist, and a longevity record will be eventually destroyed. In this article, for examining real state, a special type of binomial model based on the generalized Pareto distribution has been applied to data of Japanese centenarians. From the results, it is concluded that the upper limit of lifetime probability distribution in the Japanese population has been estimated 123 years. PMID:26362439
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).
Dodd, C.K., Jr.; 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.
Probability discounting of gains and losses: implications for risk attitudes and impulsivity.
Shead, N Will; Hodgins, David C
2009-07-01
Sixty college students performed three discounting tasks: probability discounting of gains, probability discounting of losses, and delay discounting of gains. Each task used an adjusting-amount procedure, and participants' choices affected the amount and timing of their remuneration for participating. Both group and individual discounting functions from all three procedures were well fitted by hyperboloid discounting functions. A negative correlation between the probability discounting of gains and losses was observed, consistent with the idea that individuals' choices on probability discounting tasks reflect their general attitude towards risk, regardless of whether the outcomes are gains or losses. This finding further suggests that risk attitudes reflect the weighting an individual gives to the lowest-valued outcome (e.g., getting nothing when the probabilistic outcome is a gain or actually losing when the probabilistic outcome is a loss). According to this view, risk-aversion indicates a tendency to overweight the lowest-valued outcome, whereas risk-seeking indicates a tendency to underweight it. Neither probability discounting of gains nor probability discounting of losses were reliably correlated with discounting of delayed gains, a result that is inconsistent with the idea that probability discounting and delay discounting both reflect a general tendency towards impulsivity. PMID:20119519
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.
Estimating the absolute position of a mobile robot using position probability grids
Burgard, W.; Fox, D.; Hennig, D.; Schmidt, T.
1996-12-31
In order to re-use existing models of the environment mobile robots must be able to estimate their position and orientation in such models. Most of the existing methods for position estimation are based on special purpose sensors or aim at tracking the robot`s position relative to the known starting point. This paper describes the position probability grid approach to estimating the robot`s absolute position and orientation in a metric model of the environment. Our method is designed to work with standard sensors and is independent of any knowledge about the starting point. It is a Bayesian approach based on certainty grids. In each cell of such a grid we store the probability that this cell refers to the current position of the robot. These probabilities are obtained by integrating the likelihoods of sensor readings over time. Results described in this paper show that our technique is able to reliably estimate the position of a robot in complex environments. Our approach has proven to be robust with respect to inaccurate environmental models, noisy sensors, and ambiguous situations.
NASA Astrophysics Data System (ADS)
Hengartner, Nicolas; Talbot, Lawrence; Shepherd, Ian; Bickel, Peter
1995-06-01
An important parameter in the experimental study of dynamics of combustion is the probability distribution of the effective Rayleigh scattering cross section. This cross section cannot be observed directly. Instead, pairs of measurements of laser intensities and Rayleigh scattering counts are observed. Our aim is to provide estimators for the probability density function of the scattering cross section from such measurements. The probability distribution is derived first for the number of recorded photons in the Rayleigh scattering experiment. In this approach the laser intensity measurements are treated as known covariates. This departs from the usual practice of normalizing the Rayleigh scattering counts by the laser intensities. For distributions supported on finite intervals two one based on expansion of the density in
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.
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.
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
[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. PMID:18709215
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.
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.
NASA Astrophysics Data System (ADS)
Stefanescu, E. R.; Patra, A.; Sheridan, M. F.; Cordoba, G.
2012-04-01
In this study we propose a conditional probability framework for Galeras volcano, which is one of the most active volcanoes on the world. Nearly 400,000 people currently live near the volcano; 10,000 of them reside within the zone of high volcanic hazard. Pyroclastic flows pose a major hazard for this population. Some of the questions we try to answer when studying conditional probabilities for volcanic hazards are: "Should a village be evacuated and villagers moved to a different location?", "Should we construct a road along this valley or along a different one?", "Should this university be evacuated?" Here, we try to identify critical regions such as villages, infrastructures, cities, university to determine their relative probability of inundation in case of an volcanic eruption. In this study, a set of numerical simulation were performed using a computational tool TITAN2D which simulates granular flow over digital representation of the natural terrain. The particular choice from among the methods described below can be based on the amount of information necessary in the evacuation decision and on the complexity of the analysis required in taking such decision. A set of 4200 TITAN2D runs were performed for several different location so that the area of all probably vents is covered. The output of the geophysical model provides a flow map which contains the maximum flow depth over time. Frequency approach - In estimating the conditional probability of volcanic flows we define two discrete random variables (r.v.) A and B, where P(A =1) and P(B=1) represents the probability of having a flow at location A, and B, respectively. For this analysis we choose two critical locations identified by their UTM coordinates. The flow map is then used in identifying at the pixel level, flow or non-flow at the two locations. By counting the number of times there is flow or non-flow, we are able to find the marginal probabilities along with the joint probability associated with an
Howe, Chanelle J.; Cole, Stephen R.; Chmiel, Joan S.; Muñoz, Alvaro
2011-01-01
In time-to-event analyses, artificial censoring with correction for induced selection bias using inverse probability-of-censoring weights can be used to 1) examine the natural history of a disease after effective interventions are widely available, 2) correct bias due to noncompliance with fixed or dynamic treatment regimens, and 3) estimate survival in the presence of competing risks. Artificial censoring entails censoring participants when they meet a predefined study criterion, such as exposure to an intervention, failure to comply, or the occurrence of a competing outcome. Inverse probability-of-censoring weights use measured common predictors of the artificial censoring mechanism and the outcome of interest to determine what the survival experience of the artificially censored participants would be had they never been exposed to the intervention, complied with their treatment regimen, or not developed the competing outcome. Even if all common predictors are appropriately measured and taken into account, in the context of small sample size and strong selection bias, inverse probability-of-censoring weights could fail because of violations in assumptions necessary to correct selection bias. The authors used an example from the Multicenter AIDS Cohort Study, 1984–2008, regarding estimation of long-term acquired immunodeficiency syndrome-free survival to demonstrate the impact of violations in necessary assumptions. Approaches to improve correction methods are discussed. PMID:21289029
Weighted least square estimates of the parameters of a model of survivorship probabilities.
Mitra, S
1987-06-01
"A weighted regression has been fitted to estimate the parameters of a model involving functions of survivorship probability and age. Earlier, the parameters were estimated by the method of ordinary least squares and the results were very encouraging. However, a multiple regression equation passing through the origin has been found appropriate for the present model from statistical consideration. Fortunately, this method, while methodologically more sophisticated, has a slight edge over the former as evidenced by the respective measures of reproducibility in the model and actual life tables selected for this study." PMID:12281212
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. PMID:25860540
Bernasconi, Davide Paolo; Rebora, Paola; Iacobelli, Simona; Valsecchi, Maria Grazia; Antolini, Laura
2016-03-30
The 'landmark' and 'Simon and Makuch' non-parametric estimators of the survival function are commonly used to contrast the survival experience of time-dependent treatment groups in applications such as stem cell transplant versus chemotherapy in leukemia. However, the theoretical survival functions corresponding to the second approach were not clearly defined in the literature, and the use of the 'Simon and Makuch' estimator was criticized in the biostatistical community. Here, we review the 'landmark' approach, showing that it focuses on the average survival of patients conditional on being failure free and on the treatment status assessed at the landmark time. We argue that the 'Simon and Makuch' approach represents counterfactual survival probabilities where treatment status is forced to be fixed: the patient is thought as under chemotherapy without possibility to switch treatment or as under transplant since the beginning of the follow-up. We argue that the 'Simon and Makuch' estimator leads to valid estimates only under the Markov assumption, which is however less likely to occur in practical applications. This motivates the development of a novel approach based on time rescaling, which leads to suitable estimates of the counterfactual probabilities in a semi-Markov process. The method is also extended to deal with a fixed landmark time of interest. Copyright © 2015 John Wiley & Sons, Ltd. PMID:26503800
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.
NASA Astrophysics Data System (ADS)
Meluzzi, Dario; Arya, Gaurav
2015-02-01
The estimation of contact probabilities (CP) from conformations of simulated bead-chain polymer models is a key step in methods that aim to elucidate the spatial organization of chromatin from analysis of experimentally determined contacts between different genomic loci. Although CPs can be estimated simply by counting contacts between beads in a sample of simulated chain conformations, reliable estimation of small CPs through this approach requires a large number of conformations, which can be computationally expensive to obtain. Here we describe an alternative computational method for estimating relatively small CPs without requiring large samples of chain conformations. In particular, we estimate the CPs from functional approximations to the cumulative distribution function (cdf) of the inter-bead distance for each pair of beads. These cdf approximations are obtained by fitting the extended generalized lambda distribution (EGLD) to inter-bead distances determined from a sample of chain conformations, which are in turn generated by Monte Carlo simulations. We find that CPs estimated from fitted EGLD cdfs are significantly more accurate than CPs estimated using contact counts from samples of limited size, and are more precise with all sample sizes, permitting as much as a tenfold reduction in conformation sample size for chains of 200 beads and samples smaller than 105 conformations. This method of CP estimation thus has potential to accelerate computational efforts to elucidate the spatial organization of chromatin.
Meluzzi, Dario; Arya, Gaurav
2015-02-18
The estimation of contact probabilities (CP) from conformations of simulated bead-chain polymer models is a key step in methods that aim to elucidate the spatial organization of chromatin from analysis of experimentally determined contacts between different genomic loci. Although CPs can be estimated simply by counting contacts between beads in a sample of simulated chain conformations, reliable estimation of small CPs through this approach requires a large number of conformations, which can be computationally expensive to obtain. Here we describe an alternative computational method for estimating relatively small CPs without requiring large samples of chain conformations. In particular, we estimate the CPs from functional approximations to the cumulative distribution function (cdf) of the inter-bead distance for each pair of beads. These cdf approximations are obtained by fitting the extended generalized lambda distribution (EGLD) to inter-bead distances determined from a sample of chain conformations, which are in turn generated by Monte Carlo simulations. We find that CPs estimated from fitted EGLD cdfs are significantly more accurate than CPs estimated using contact counts from samples of limited size, and are more precise with all sample sizes, permitting as much as a tenfold reduction in conformation sample size for chains of 200 beads and samples smaller than 10(5) conformations. This method of CP estimation thus has potential to accelerate computational efforts to elucidate the spatial organization of chromatin. PMID:25563926
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.
NASA Astrophysics Data System (ADS)
Eleftheriadou, Anastasia K.; Baltzopoulou, Aikaterini D.; Karabinis, Athanasios I.
2016-04-01
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.
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
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. PMID:16506435
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.
IMPROVED RISK ESTIMATES FOR CARBON TETRACHLORIDE
Carbon tetrachloride (CCl4) has been used extensively within the Department of Energy (DOE) nuclear weapons facilities. Costs associated with cleanup of CCl4 at DOE facilities are driven by current cancer risk estimates which assume CCl4 is a genotoxic carcinogen. However, a grow...
NASA Astrophysics Data System (ADS)
Lee, T. S.; Yoon, S.; Jeong, C.
2012-12-01
The primary purpose of frequency analysis in hydrology is to estimate the magnitude of an event with a given frequency of occurrence. The precision of frequency analysis depends on the selection of an appropriate probability distribution model (PDM) and parameter estimation techniques. A number of PDMs have been developed to describe the probability distribution of the hydrological variables. For each of the developed PDMs, estimated parameters are provided based on alternative estimation techniques, such as the method of moments (MOM), probability weighted moments (PWM), linear function of ranked observations (L-moments), and maximum likelihood (ML). Generally, the results using ML are more reliable than the other methods. However, the ML technique is more laborious than the other methods because an iterative numerical solution, such as the Newton-Raphson method, must be used for the parameter estimation of PDMs. In the meantime, meta-heuristic approaches have been developed to solve various engineering optimization problems (e.g., linear and stochastic, dynamic, nonlinear). These approaches include genetic algorithms, ant colony optimization, simulated annealing, tabu searches, and evolutionary computation methods. Meta-heuristic approaches use a stochastic random search instead of a gradient search so that intricate derivative information is unnecessary. Therefore, the meta-heuristic approaches have been shown to be a useful strategy to solve optimization problems in hydrology. A number of studies focus on using meta-heuristic approaches for estimation of hydrological variables with parameter estimation of PDMs. Applied meta-heuristic approaches offer reliable solutions but use more computation time than derivative-based methods. Therefore, the purpose of this study is to enhance the meta-heuristic approach for the parameter estimation of PDMs by using a recently developed algorithm known as a harmony search (HS). The performance of the HS is compared to the
Secondary prevention and estimation of fracture risk.
Mitchell, Paul James; Chem, C
2013-12-01
The key questions addressed in this chapter are: • How can individual risk of fracture be best estimated? • What is the best system to prevent a further fracture? • How to implement systems for preventing further fractures? Absolute fracture risk calculators (FRCs) provide a means to estimate an individual's future fracture risk. FRCs are widely available and provide clinicians and patients a platform to discuss the need for intervention to prevent fragility fractures. Despite availability of effective osteoporosis medicines for almost two decades, most patients presenting with new fragility fractures do not receive secondary preventive care. The Fracture Liaison Service (FLS) model has been shown in a number of countries to eliminate the care gap in a clinically and cost-effective manner. Leading international and national organisations have developed comprehensive resources and/or national strategy documents to provide guidance on implementation of FLS in local, regional and national health-care systems. PMID:24836336
An estimate of the probability of capture of a binary star by a supermassive black hole
NASA Astrophysics Data System (ADS)
Dremova, G. N.; Dremov, V. V.; Tutukov, A. V.
2016-08-01
A simple model for the dynamics of stars located in a sphere with a radius of one-tenth of the central parsec, designed to enable estimation of the probability of capture in the close vicinity ( r < 10-3 pc) of a supermassive black hole (SMBH) is presented. In the case of binary stars, such a capture with a high probability results in the formation of a hyper-velocity star. The population of stars in a sphere of radius <0.1 pc is calculated based on data for the Galactic rotation curve. To simulate the distortion of initially circular orbits of stars, these are subjected to a series of random shock encounters ("kicks"), whose net effect is to "push" these binary systems into the region of potential formation of hyper-velocity stars. The mean crossing time of the border of the close vicinity of the SMBH ( r < 10-3 pc) by the stellar orbit can be used to estimate the probability that a binary system is captured, followed by the possible ejection of a hyper-velocity star.
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.
Caballero, Karla; Akella, Ram
2015-01-01
In this paper, we propose a framework to dynamically estimate the probability that a patient is readmitted after he is discharged from the ICU and transferred to a lower level care. We model this probability as a latent state which evolves over time using Dynamical Linear Models (DLM). We use as an input a combination of numerical and text features obtained from the patient Electronic Medical Records (EMRs). We process the text from the EMRs to capture different diseases, symptoms and treatments by means of noun phrases and ontologies. We also capture the global context of each text entry using Statistical Topic Models. We fill out the missing values using a Expectation Maximization based method (EM). Experimental results show that our method outperforms other methods in the literature terms of AUC, sensitivity and specificity. In addition, we show that the combination of different features (numerical and text) increases the prediction performance of the proposed approach. PMID:26958282
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.
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).
ERIC Educational Resources Information Center
HUDMAN, JOHN T.; ZABROWSKI, EDWARD K.
EQUATIONS FOR SYSTEM INTAKE, DROPOUT, AND RETENTION RATE CALCULATIONS ARE DERIVED FOR ELEMENTARY SCHOOLS, SECONDARY SCHOOLS, AND COLLEGES. THE PROCEDURES DESCRIBED WERE FOLLOWED IN DEVELOPING ESTIMATES OF SELECTED ELEMENTS OF THE TRANSITION PROBABILITY MATRICES USED IN DYNAMOD II. THE PROBABILITY MATRIX CELLS ESTIMATED BY THE PROCEDURES DESCRIBED…
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.
NASA Astrophysics Data System (ADS)
Turel, N.; Arikan, F.
2010-12-01
Ionospheric channel characterization is an important task for both HF and satellite communications. The inherent space-time variability of the ionosphere can be observed through total electron content (TEC) that can be obtained using GPS receivers. In this study, within-the-hour variability of the ionosphere over high-latitude, midlatitude, and equatorial regions is investigated by estimating a parametric model for the probability density function (PDF) of GPS-TEC. PDF is a useful tool in defining the statistical structure of communication channels. For this study, a half solar cycle data is collected for 18 GPS stations. Histograms of TEC, corresponding to experimental probability distributions, are used to estimate the parameters of five different PDFs. The best fitting distribution to the TEC data is obtained using the maximum likelihood ratio of the estimated parametric distributions. It is observed that all of the midlatitude stations and most of the high-latitude and equatorial stations are distributed as lognormal. A representative distribution can easily be obtained for stations that are located in midlatitude using solar zenith normalization. The stations located in very high latitudes or in equatorial regions cannot be described using only one PDF distribution. Due to significant seasonal variability, different distributions are required for summer and winter.
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.
Mondschean, T H
1986-01-01
"This article develops a method for estimating the probability of emigration conditional on the observed characteristics of individuals. In addition, it is shown how to calculate the mean, standard error, and confidence intervals of the conditional probability of emigration given a random sample of emigrants. The technique is illustrated by providing statistically consistent estimates of the probability an Italian would emigrate to the United States in 1901 and 1911, conditional on personal attributes." PMID:12340643
Taylor, J. F.; Abbitt, B.; Walter, J. P.; Davis, S. K.; Jaques, J. T.; Ochoa, R. F.
1993-01-01
β-Mannosidosis is a lethal lysosomal storage disease inherited as an autosomal recessive in man, cattle and goats. Laboratory assay data of plasma β-mannosidase activity represent a mixture of homozygous normal and carrier genotype distributions in a proportion determined by genotype frequency. A maximum likelihood approach employing data transformations for each genotype distribution and assuming a diallelic model of inheritance is described. Estimates of the transformation and genotype distribution parameters, gene frequency, genotype fitness and carrier probability were obtained simultaneously from a sample of 2,812 observations on U.S. purebred Salers cattle with enzyme activity, age, gender, month of pregnancy, month of testing, and parents identified. Transformations to normality were not required, estimated gene and carrier genotype frequencies of 0.074 and 0.148 were high, and the estimated relative fitness of heterozygotes was 1.36. The apparent overdominance in fitness may be due to a nonrandom sampling of progeny genotypes within families. The mean of plasma enzyme activity was higher for males than females, higher in winter months, lower in summer months and decreased with increased age. Estimates of carrier probabilities indicate that the test is most effective when animals are sampled as calves, although effectiveness of the plasma assay was less for males than females. Test effectiveness was enhanced through averaging repeated assays of enzyme activity on each animal. Our approach contributes to medical diagnostics in several ways. Rather than assume underlying normality for the distributions comprising the mixture, we estimate transformations to normality for each genotype distribution simultaneously with all other model parameters. This process also excludes potential biases due to data preadjustment for systematic effects. We also provide a method for partitioning phenotypic variation within each genotypic distribution which allows an assessment
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.
How to estimate your tolerance for risk
Mackay, J.A.
1996-12-31
Risk tolerance is used to calculate the Risk Adjusted Value (RAV) of a proposed investment. The RAV incorporates both the expected value and risk attitude for a particular investment, taking into consideration your concern for catastrophic financial loss, as well as chance of success, cost and value if successful. Uncertainty can be incorporated into all of the above variables. Often a project is more valuable to a corporation if a partial working interest is taken rather than the entire working interest. The RAV can be used to calculate the optimum working interest and the value of that diversification. To estimate the Apparent Risk Tolerance (ART) of an individual, division or corporation several methods can be employed: (1) ART can be calculated from the working interest selected in prior investment decisions. (2) ART can be estimated from a selection of working interests by the decision maker in a proposed portfolio of projects. (3) ART can be approximated from data released to the Security and Exchange Commission (SEC) in the annual 10K supplements (for both your company and possible partners). (4) ART can be assigned based on corporate size, budget, or activity. Examples are provided for the various methods to identify risk tolerance and apply it in making optimum working interest calculations for individual projects and portfolios.
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.
On the method of logarithmic cumulants for parametric probability density function estimation.
Krylov, Vladimir A; Moser, Gabriele; Serpico, Sebastiano B; Zerubia, Josiane
2013-10-01
Parameter estimation of probability density functions is one of the major steps in the area of statistical image and signal processing. In this paper we explore several properties and limitations of the recently proposed method of logarithmic cumulants (MoLC) parameter estimation approach which is an alternative to the classical maximum likelihood (ML) and method of moments (MoM) approaches. We derive the general sufficient condition for a strong consistency of the MoLC estimates which represents an important asymptotic property of any statistical estimator. This result enables the demonstration of the strong consistency of MoLC estimates for a selection of widely used distribution families originating from (but not restricted to) synthetic aperture radar image processing. We then derive the analytical conditions of applicability of MoLC to samples for the distribution families in our selection. Finally, we conduct various synthetic and real data experiments to assess the comparative properties, applicability and small sample performance of MoLC notably for the generalized gamma and K families of distributions. Supervised image classification experiments are considered for medical ultrasound and remote-sensing SAR imagery. The obtained results suggest that MoLC is a feasible and computationally fast yet not universally applicable alternative to MoM. MoLC becomes especially useful when the direct ML approach turns out to be unfeasible. PMID:23799694
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)
Mazzoleni, Maurizio; Brandimarte, Luigia; Barontini, Stefano; Ranzi, Roberto
2014-05-01
Over the centuries many societies have preferred to settle down nearby floodplains area and take advantage of the favorable environmental conditions. Due to changing hydro-meteorological conditions, over time, levee systems along rivers have been raised to protect urbanized area and reduce the impact of floods. As expressed by the so called "levee paradox", many societies might to tend to trust these levee protection systems due to an induced sense of safety and, as a consequence, invest even more in urban developing in levee protected flood prone areas. As a result, considering also the increasing number of population around the world, people living in floodplains is growing. However, human settlements in floodplains are not totally safe and have been continuously endangered by the risk of flooding. In fact, failures of levee system in case of flood event have also produced the most devastating disasters of the last two centuries due to the exposure of the developed floodprone areas to risk. In those cases, property damage is certain, but loss of life can vary dramatically with the extent of the inundation area, the size of the population at risk, and the amount of warning time available. The aim of this study is to propose an innovative methodology to estimate the reliability of a general river levee system in case of piping, considering different sources of uncertainty, and analyze the influence of different discretization of the river reach in sub-reaches in the evaluation of the probability of failure. The reliability analysis, expressed in terms of fragility curve, was performed evaluating the probability of failure, conditioned by a given hydraulic load in case of a certain levee failure mechanism, using a Monte Carlo and First Order Reliability Method. Knowing the information about fragility curve for each discrete levee reach, different fragility indexes were introduced. Using the previous information was then possible to classify the river into sub
Sacks, H.K.; Novak, T.
2008-03-15
During the past decade, several methane/air explosions in abandoned or sealed areas of underground coal mines have been attributed to lightning. Previously published work by the authors showed, through computer simulations, that currents from lightning could propagate down steel-cased boreholes and ignite explosive methane/air mixtures. The presented work expands on the model and describes a methodology based on IEEE Standard 1410-2004 to estimate the probability of an ignition. The methodology provides a means to better estimate the likelihood that an ignition could occur underground and, more importantly, allows the calculation of what-if scenarios to investigate the effectiveness of engineering controls to reduce the hazard. The computer software used for calculating fields and potentials is also verified by comparing computed results with an independently developed theoretical model of electromagnetic field propagation through a conductive medium.
NASA Astrophysics Data System (ADS)
Xue, Ming; Wang, Jiang; Jia, Chenhui; Yu, Haitao; Deng, Bin; Wei, Xile; Che, Yanqiu
2013-03-01
In this paper, we proposed a new approach to estimate unknown parameters and topology of a neuronal network based on the adaptive synchronization control scheme. A virtual neuronal network is constructed as an observer to track the membrane potential of the corresponding neurons in the original network. When they achieve synchronization, the unknown parameters and topology of the original network are obtained. The method is applied to estimate the real-time status of the connection in the feedforward network and the neurotransmitter release probability of unreliable synapses is obtained by statistic computation. Numerical simulations are also performed to demonstrate the effectiveness of the proposed adaptive controller. The obtained results may have important implications in system identification in neural science.
ANNz2 - Photometric redshift and probability density function estimation using machine-learning
NASA Astrophysics Data System (ADS)
Sadeh, Iftach
2014-05-01
Large photometric galaxy surveys allow the study of questions at the forefront of science, such as the nature of dark energy. The success of such surveys depends on the ability to measure the photometric redshifts of objects (photo-zs), based on limited spectral data. A new major version of the public photo-z estimation software, ANNz , is presented here. The new code incorporates several machine-learning methods, such as artificial neural networks and boosted decision/regression trees, which are all used in concert. The objective of the algorithm is to dynamically optimize the performance of the photo-z estimation, and to properly derive the associated uncertainties. In addition to single-value solutions, the new code also generates full probability density functions in two independent ways.
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
Estimation of (n,f) Cross-Sections by Measuring Reaction Probability Ratios
Plettner, C; Ai, H; Beausang, C W; Bernstein, L A; Ahle, L; Amro, H; Babilon, M; Burke, J T; Caggiano, J A; Casten, R F; Church, J A; Cooper, J R; Crider, B; Gurdal, G; Heinz, A; McCutchan, E A; Moody, K; Punyon, J A; Qian, J; Ressler, J J; Schiller, A; Williams, E; Younes, W
2005-04-21
Neutron-induced reaction cross-sections on unstable nuclei are inherently difficult to measure due to target activity and the low intensity of neutron beams. In an alternative approach, named the 'surrogate' technique, one measures the decay probability of the same compound nucleus produced using a stable beam on a stable target to estimate the neutron-induced reaction cross-section. As an extension of the surrogate method, in this paper they introduce a new technique of measuring the fission probabilities of two different compound nuclei as a ratio, which has the advantage of removing most of the systematic uncertainties. This method was benchmarked in this report by measuring the probability of deuteron-induced fission events in coincidence with protons, and forming the ratio P({sup 236}U(d,pf))/P({sup 238}U(d,pf)), which serves as a surrogate for the known cross-section ratio of {sup 236}U(n,f)/{sup 238}U(n,f). IN addition, the P({sup 238}U(d,d{prime}f))/P({sup 236}U(d,d{prime}f)) ratio as a surrogate for the {sup 237}U(n,f)/{sup 235}U(n,f) cross-section ratio was measured for the first time in an unprecedented range of excitation energies.
Inconsistent probability estimates of a hypothesis: the role of contrasting support.
Bonini, Nicolao; Gonzalez, Michel
2005-01-01
This paper studies consistency in the judged probability of a target hypothesis in lists of mutually exclusive nonexhaustive hypotheses. Specifically, it controls the role played by the support of displayed competing hypotheses and the relatedness between the target hypothesis and its alternatives. Three experiments are reported. In all experiments, groups of people were presented with a list of mutually exclusive nonexhaustive causes of a person's death. In the first two experiments, they were asked to judge the probability of each cause as that of the person's decease. In the third experiment, people were asked for a frequency estimation task. Target causes were presented in all lists. Several other alternative causes to the target ones differed across the lists. Findings show that the judged probability/frequency of a target cause changes as a function of the support of the displayed competing causes. Specifically, it is higher when its competing displayed causes have low rather than high support. Findings are consistent with the contrastive support hypothesis within the support theory. PMID:15779531
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.
Lahodny, G E; Gautam, R; Ivanek, R
2015-01-01
Indirect transmission through the environment, pathogen shedding by infectious hosts, replication of free-living pathogens within the environment, and environmental decontamination are suspected to play important roles in the spread and control of environmentally transmitted infectious diseases. To account for these factors, the classic Susceptible-Infectious-Recovered-Susceptible epidemic model is modified to include a compartment representing the amount of free-living pathogen within the environment. The model accounts for host demography, direct and indirect transmission, replication of free-living pathogens in the environment, and removal of free-living pathogens by natural death or environmental decontamination. Based on the assumptions of the deterministic model, a continuous-time Markov chain model is developed. An estimate for the probability of disease extinction or a major outbreak is obtained by approximating the Markov chain with a multitype branching process. Numerical simulations illustrate important differences between the deterministic and stochastic counterparts, relevant for outbreak prevention, that depend on indirect transmission, pathogen shedding by infectious hosts, replication of free-living pathogens, and environmental decontamination. The probability of a major outbreak is computed for salmonellosis in a herd of dairy cattle as well as cholera in a human population. An explicit expression for the probability of disease extinction or a major outbreak in terms of the model parameters is obtained for systems with no direct transmission or replication of free-living pathogens. PMID:25198247
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.
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
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
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. PMID:24989843
Johnson, W.R.; Marshall, C.F.; Anderson, C.M.; Lear, E.M.
1994-08-01
The Federal Government has proposed to offer Outer Continental Shelf (OCS) lands in Cook Inlet for oil and gas leasing. Because oil spills may occur from activities associated with offshore oil production, the Minerals Management Service conducts a formal risk assessment. In evaluating the significance of accidental oil spills, it is important to remember that the occurrence of such spills is fundamentally probabilistic. The effects of oil spills that could occur during oil and gas production must be considered. This report summarizes results of an oil-spill risk analysis conducted for the proposed Cook Inlet OCS Lease Sale 149. The objective of this analysis was to estimate relative risks associated with oil and gas production for the proposed lease sale. To aid the analysis, conditional risk contour maps of seasonal conditional probabilities of spill contact were generated for each environmental resource or land segment in the study area. This aspect is discussed in this volume of the two volume report.
Estimation of drought transition probabilities in Sicily making use of exogenous variables
NASA Astrophysics Data System (ADS)
Bonaccorso, Brunella; di Mauro, Giuseppe; Cancelliere, Antonino; Rossi, Giuseppe
2010-05-01
Drought monitoring and forecasting play a very important role for an effective drought management. A timely monitoring of drought features and/or forecasting of an incoming drought do make possible an effective mitigation of its impacts, more than in the case of other natural disasters (e.g. floods, earthquakes, hurricanes, etc.). An accurate selection of indices, able to monitor the main characteristics of droughts, is essential to help decision makers to implement appropriate preparedness and mitigation measures. Among the several proposed indices for drought monitoring, the Standardized Precipitation Index (SPI) has found widespread use to monitor dry and wet periods of precipitation aggregated at different time scales. Recently, some efforts have been made to analyze the role of SPI for drought forecasting, as well as to estimate transition probabilities between drought classes. In the present work, a model able to estimate transition probabilities from a current SPI drought class or from a current SPI value to future classes, corresponding to droughts of different severities, is presented and extended in order to include information provided by an exogenous variable, such as a large scale climatic index as the North Atlantic Oscillation Index (NAO). The model has been preliminarily applied and tested with reference to SPI series computed on average areal precipitation in Sicily island, Italy, making use of NAO as exogenous variable. Results seem to indicate that winter drought transition probabilities in Sicily are generally affected by NAO index. Furthermore, the statistical significance of such influence has been tested by means of a Montecarlo analysis, which indicates that the effect of NAO on drought transition in Sicily should be considered significant.
NASA Astrophysics Data System (ADS)
Samejima, Masaki; Negoro, Keisuke; Mitsukuni, Koshichiro; Akiyoshi, Masanori
We propose a finding method of business risk factors on qualitative and quantitative hybrid simulation in time series. Effect ratios of qualitative arcs in the hybrid simulation vary output values of the simulation, so we define effect ratios causing risk as business risk factors. Finding business risk factors in entire ranges of effect ratios is time-consuming. It is considered that probability distributions of effect ratios in present time step and ones in previous time step are similar, the probability distributions in present time step can be estimated. Our method finds business risk factors in only estimated ranges effectively. Experimental results show that a precision rate and a recall rate are 86%, and search time is decreased 20% at least.
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.
Nonparametric estimation with recurrent competing risks data
Peña, Edsel A.
2014-01-01
Nonparametric estimators of component and system life distributions are developed and presented for situations where recurrent competing risks data from series systems are available. The use of recurrences of components’ failures leads to improved efficiencies in statistical inference, thereby leading to resource-efficient experimental or study designs or improved inferences about the distributions governing the event times. Finite and asymptotic properties of the estimators are obtained through simulation studies and analytically. The detrimental impact of parametric model misspecification is also vividly demonstrated, lending credence to the virtue of adopting nonparametric or semiparametric models, especially in biomedical settings. The estimators are illustrated by applying them to a data set pertaining to car repairs for vehicles that were under warranty. PMID:24072583
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.
Grossi, Enzo
2005-01-01
Background The concept of risk has pervaded medical literature in the last decades and has become a familiar topic, and the concept of probability, linked to binary logic approach, is commonly applied in epidemiology and clinical medicine. The application of probability theory to groups of individuals is quite straightforward but can pose communication challenges at individual level. Few articles by the way have tried to focus the concept of "risk" at the individual subject level rather than at population level. Discussion The author has reviewed the conceptual framework which has led to the use of probability theory in the medical field in a time when the principal causes of death were represented by acute disease often of infective origin. In the present scenario, in which chronic degenerative disease dominate and there are smooth transitions between health and disease the use of fuzzy logic rather than binary logic would be more appropriate. The use of fuzzy logic in which more than two possible truth-value assignments are allowed overcomes the trap of probability theory when dealing with uncertain outcomes, thereby making the meaning of a certain prognostic statement easier to understand by the patient. Summary At individual subject level the recourse to the term plausibility, related to fuzzy logic, would help the physician to communicate to the patient more efficiently in comparison with the term probability, related to binary logic. This would represent an evident advantage for the transfer of medical evidences to individual subjects. PMID:16188041
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
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
Accretion of Fine Particles: Sticking Probability Estimated by Optical Sizing of Fractal Aggregates
NASA Astrophysics Data System (ADS)
Sugiura, N.; Higuchi, Y.
1993-07-01
Sticking probability of fine particles is an important parameter that determines (1) the settling of fine particles to the equatorial plane of the solar nebula and hence the formation of planetesimals, and (2) the thermal structure of the nebula, which is dependent on the particle size through opacity. It is generally agreed that the sticking probability is 1 for submicrometer particles, but at sizes larger than 1 micrometer, there exist almost no data on the sticking probability. A recent study [1] showed that aggregates (with radius from 0.2 to 2 mm) did not stick when collided at a speed of 0.15 to 4 m/s. Therefore, somewhere between 1 micrometer and 200 micrometers, sticking probabilities of fine particles change from nearly 1 to nearly 0. We have been studying [2,3] sticking probabilities of dust aggregates in this size range using an optical sizing method. The optical sizing method has been well established for spherical particles. This method utilizes the fact that the smaller the size, the larger the angle of the scattered light. For spheres with various sizes, the size distribution is determined by solving Y(i) = M(i,j)X(j), where Y(i) is the scattered light intensity at angle i, X(j) is the number density of spheres with size j, and M(i,j) is the scattering matrix, which is determined by Mie theory. Dust aggregates, which we expect to be present in the early solar nebula, are not solid spheres, but probably have a porous fractal structure. For such aggregates the scattering matrix M(i,j) must be determined by taking account of all the interaction among constituent particles (discrete dipole approximation). Such calculation is possible only for very small aggregates, and for larger aggregates we estimate the scattering matrix by extrapolation, assuming that the fractal nature of the aggregates allows such extrapolation. In the experiments using magnesium oxide fine particles floating in a chamber at ambient pressure, the size distribution (determined by
Dynamic probability control limits for risk-adjusted Bernoulli CUSUM charts.
Zhang, Xiang; Woodall, William H
2015-11-10
The risk-adjusted Bernoulli cumulative sum (CUSUM) chart developed by Steiner et al. (2000) is an increasingly popular tool for monitoring clinical and surgical performance. In practice, however, the use of a fixed control limit for the chart leads to a quite variable in-control average run length performance for patient populations with different risk score distributions. To overcome this problem, we determine simulation-based dynamic probability control limits (DPCLs) patient-by-patient for the risk-adjusted Bernoulli CUSUM charts. By maintaining the probability of a false alarm at a constant level conditional on no false alarm for previous observations, our risk-adjusted CUSUM charts with DPCLs have consistent in-control performance at the desired level with approximately geometrically distributed run lengths. Our simulation results demonstrate that our method does not rely on any information or assumptions about the patients' risk distributions. The use of DPCLs for risk-adjusted Bernoulli CUSUM charts allows each chart to be designed for the corresponding particular sequence of patients for a surgeon or hospital. PMID:26037959
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. PMID:16764268
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.
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.
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.
Carr, J.R. . Dept. of Geological Sciences); Mao, Nai-hsien )
1992-01-01
Disjunctive kriging has been compared previously to multigaussian kriging and indicator cokriging for estimation of cumulative distribution functions; it has yet to be compared extensively to probability kriging. Herein, disjunctive kriging and generalized probability kriging are applied to one real and one simulated data set and compared for estimation of the cumulative distribution functions. Generalized probability kriging is an extension, based on generalized cokriging theory, of simple probability kriging for the estimation of the indicator and uniform transforms at each cutoff, Z{sub k}. The disjunctive kriging and the generalized probability kriging give similar results for simulated data of normal distribution, but differ considerably for real data set with non-normal distribution.
Reexamination of spent fuel shipment risk estimates
COOK,J.R.; SPRUNG,JEREMY L.
2000-04-25
The risks associated with the transport of spent nuclear fuel by truck and rail have been reexamined and compared to results published in NUREG-O170 and the Modal Study. The full reexamination considered transport of PWR and BWR spent fuel by truck and rail in four generic Type B spent fuel casks. Because they are typical, this paper presents results only for transport of PWR spent fuel in steel-lead steel casks. Cask and spent fuel response to collision impacts and fires were evaluated by performing three-dimensional finite element and one-dimensional heat transport calculations. Accident release fractions were developed by critical review of literature data. Accident severity fractions were developed from Modal Study truck and rail accident event trees, modified to reflect the frequency of occurrence of hard and soft rock wayside route surfaces as determined by analysis of geographic data. Incident-free population doses and the population dose risks associated with the accidents that might occur during transport were calculated using the RADTRAN 5 transportation risk code. The calculated incident-free doses were compared to those published in NUREG-O170. The calculated accident dose risks were compared to dose risks calculated using NUREG-0170 and Modal Study accident source terms. The comparisons demonstrated that both of these studies made a number of very conservative assumptions about spent fuel and cask response to accident conditions, which caused their estimates of accident source terms, accident frequencies, and accident consequences to also be very conservative. The results of this study and the previous studies demonstrate that the risks associated with the shipment of spent fuel by truck or rail are very small.
Wenger, S.J.; Freeman, Mary C.
2008-01-01
Researchers have developed methods to account for imperfect detection of species with either occupancy (presence-absence) or count data using replicated sampling. We show how these approaches can be combined to simultaneously estimate occurrence, abundance, and detection probability by specifying a zero-inflated distribution for abundance. This approach may be particularly appropriate when patterns of occurrence and abundance arise from distinct processes operating at differing spatial or temporal scales. We apply the model to two data sets: (1) previously published data for a species of duck, Anas platyrhynchos, and (2) data for a stream fish species, Etheostoma scotti. We show that in these cases, an incomplete-detection zero-inflated modeling approach yields a superior fit to the data than other models. We propose that zero-inflated abundance models accounting for incomplete detection be considered when replicate count data are available.
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
NASA Astrophysics Data System (ADS)
Skripnichenko, P.; Galushina, T.; Loginova, M.
2015-08-01
This work is devoted to the description of the software EROS (Ephemeris Research and Observation Services), which is being developed both by the astronomy department of Ural Federal University and Tomsk State University. This software provides the ephemeris support for the positional observations. The most interesting feature of the software is an automatization of all the processes preparation for observations from the determination of the night duration to the ephemeris calculation and forming of a program observation schedule. The accuracy of ephemeris calculation mostly depends on initial data precision that defined from errors of observations which used to determination of orbital elements. In the case if object has a small number of observations which spread at short arc of orbit there is a real necessity to calculate not only at nominal orbit but probability domain both. In this paper under review ephemeris we will be understand a field on the celestial sphere which calculated based on the probability domain. Our software EROS has a relevant functional for estimation of review ephemeris. This work contains description of software system and results of the program using.
Estimating the ground-state probability of a quantum simulation with product-state measurements
NASA Astrophysics Data System (ADS)
Yoshimura, Bryce; Freericks, James
2015-10-01
.One of the goals in quantum simulation is to adiabatically generate the ground state of a complicated Hamiltonian by starting with the ground state of a simple Hamiltonian and slowly evolving the system to the complicated one. If the evolution is adiabatic and the initial and final ground states are connected due to having the same symmetry, then the simulation will be successful. But in most experiments, adiabatic simulation is not possible because it would take too long, and the system has some level of diabatic excitation. In this work, we quantify the extent of the diabatic excitation even if we do not know a priori what the complicated ground state is. Since many quantum simulator platforms, like trapped ions, can measure the probabilities to be in a product state, we describe techniques that can employ these simple measurements to estimate the probability of being in the ground state of the system after the diabatic evolution. These techniques do not require one to know any properties about the Hamiltonian itself, nor to calculate its eigenstate properties. All the information is derived by analyzing the product-state measurements as functions of time.
Smith, L.L.; Barichivich, W.J.; Staiger, J.S.; Smith, Kimberly G.; Dodd, C.K., Jr.
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
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.
Relating space radiation environments to risk estimates
Curtis, S.B. ||
1993-12-31
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.
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.
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
Estimating Effect Sizes and Expected Replication Probabilities from GWAS Summary Statistics
Holland, Dominic; Wang, Yunpeng; Thompson, Wesley K.; Schork, Andrew; Chen, Chi-Hua; Lo, Min-Tzu; Witoelar, Aree; Werge, Thomas; O'Donovan, Michael; Andreassen, Ole A.; Dale, Anders M.
2016-01-01
Genome-wide Association Studies (GWAS) result in millions of summary statistics (“z-scores”) for single nucleotide polymorphism (SNP) associations with phenotypes. These rich datasets afford deep insights into the nature and extent of genetic contributions to complex phenotypes such as psychiatric disorders, which are understood to have substantial genetic components that arise from very large numbers of SNPs. The complexity of the datasets, however, poses a significant challenge to maximizing their utility. This is reflected in a need for better understanding the landscape of z-scores, as such knowledge would enhance causal SNP and gene discovery, help elucidate mechanistic pathways, and inform future study design. Here we present a parsimonious methodology for modeling effect sizes and replication probabilities, relying only on summary statistics from GWAS substudies, and a scheme allowing for direct empirical validation. We show that modeling z-scores as a mixture of Gaussians is conceptually appropriate, in particular taking into account ubiquitous non-null effects that are likely in the datasets due to weak linkage disequilibrium with causal SNPs. The four-parameter model allows for estimating the degree of polygenicity of the phenotype and predicting the proportion of chip heritability explainable by genome-wide significant SNPs in future studies with larger sample sizes. We apply the model to recent GWAS of schizophrenia (N = 82,315) and putamen volume (N = 12,596), with approximately 9.3 million SNP z-scores in both cases. We show that, over a broad range of z-scores and sample sizes, the model accurately predicts expectation estimates of true effect sizes and replication probabilities in multistage GWAS designs. We assess the degree to which effect sizes are over-estimated when based on linear-regression association coefficients. We estimate the polygenicity of schizophrenia to be 0.037 and the putamen to be 0.001, while the respective sample sizes
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.
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.
Launch Risk Acceptability Considering Uncertainty in Risk Estimates
NASA Astrophysics Data System (ADS)
Collins, J. D.; Carbon, S. L.
2010-09-01
Quantification of launch risk is difficult and uncertain due to the assumptions made in the modeling process and the difficulty in developing the supporting data. This means that estimates of the risks are uncertain and the decision maker must decide on the acceptability of the launch under uncertainty. This paper describes the process to quantify the uncertainty and, in the process, describes the separate roles of aleatory and epistemic uncertainty in obtaining the point estimate of the casualty expectation and, ultimately, the distribution of the uncertainty in the computed casualty expectation. Tables are included of the significant sources and the nature of the contributing uncertainties. In addition, general procedures and an example are also included to describe the computational procedure. The second part of the paper discusses how the quantified uncertainty should be applied to the decision-making process. This discussion describes the procedure proposed and adopted by the Risk Committee of the Range Commander’s Council Range Safety Group which will be published in RCC 321-10 [1].
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.
Chandra, A; Rudraiah, L; Zalenski, R J
2001-02-01
In summary, this article focused on the use of stress testing to risk-stratify patients at the conclusion of their emergency evaluation for ACI. As discussed, those patients in the probably not ACI category require additional risk stratification prior to discharge. It should be kept in mind that patients in this category are heterogeneous, containing subgroups at both higher and lower risk of ACI and cardiac events. The patients with lower pretest probability for ACI may only need exercise testing in the ED. Patients with higher pretest probability should undergo myocardial perfusion or echocardiographic stress testing to maximize diagnostic and prognostic information. Prognostic information is the key to provocative testing in the ED. Prognostic information is the component that will help emergency physicians identify the patients who may be discharged home safely without having to worry about a 6% annual cardiac death rate and a 10% overall death rate over the next 30 months. Stress testing provides this key prognostic data, and it can be obtained in short-stay chest pain observation units in a safe, timely, and cost-effective fashion. PMID:11214405
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.
Estimating Risk of Alcohol Dependence Using Alcohol Screening Scores*
Rubinsky, Anna D.; Kivlahan, Daniel R.; Volk, Robert J.; Maynard, Charles; Bradley, Katharine A.
2010-01-01
Brief alcohol counseling interventions can reduce alcohol consumption and related morbidity among non-dependent risky drinkers, but more intensive alcohol treatment is recommended for persons with alcohol dependence. This study evaluated whether scores on common alcohol screening tests could identify patients likely to have current alcohol dependence so that more appropriate follow-up assessment and/or intervention could be offered. This cross-sectional study used secondary data from 392 male and 927 female adult family medicine outpatients (1993–1994). Likelihood ratios were used to empirically identify and evaluate ranges of scores of the AUDIT, the AUDIT-C, two single-item questions about frequency of binge drinking, and the CAGE questionnaire for detecting DSM-IV past-year alcohol dependence. Based on the prevalence of past-year alcohol dependence in this sample (men: 12.2%; women: 5.8%), zones of the AUDIT and AUDIT-C identified wide variability in the post-screening risk of alcohol dependence in men and women, even among those who screened positive for alcohol misuse. Among men, AUDIT zones 5–10, 11–14 and 15–40 were associated with post-screening probabilities of past-year alcohol dependence ranging from 18–87%, and AUDIT-C zones 5–6, 7–9 and 10–12 were associated with probabilities ranging from 22–75%. Among women, AUDIT zones 3–4, 5–8, 9–12 and 13–40 were associated with post-screening probabilities of past-year alcohol dependence ranging from 6–94%, and AUDIT-C zones 3, 4–6, 7–9 and 10–12 were associated with probabilities ranging from 9–88%. AUDIT or AUDIT-C scores could be used to estimate the probability of past-year alcohol dependence among patients who screen positive for alcohol misuse and inform clinical decision-making. PMID:20042299
Software risk estimation and management techniques at JPL
NASA Technical Reports Server (NTRS)
Hihn, J.; Lum, K.
2002-01-01
In this talk we will discuss how uncertainty has been incorporated into the JPL software model, probabilistic-based estimates, and how risk is addressed, how cost risk is currently being explored via a variety of approaches, from traditional risk lists, to detailed WBS-based risk estimates to the Defect Detection and Prevention (DDP) tool.
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
A methodology to estimate probability of occurrence of floods using principal component analysis
NASA Astrophysics Data System (ADS)
castro Heredia, L. M.; Gironas, J. A.
2014-12-01
Flood events and debris flows are characterized by a very rapid response of basins to precipitation, often resulting in loss of life and property damage. Complex topography with steep slopes and narrow valleys increase the likelihood of having these events. An early warning system (EWS) is a tool that allows anticipating a hazardous event, which in turns provides time for an early response to reduce negative impacts. These EWS's can rely on very powerful and computer-demanding models to predict flow discharges and inundation zones, which require data typically unavailable. Instead, simpler EWŚs based on a statistical analysis of observed hydro-meteorological data could be a good alternative. In this work we propose a methodology for estimating the probability of exceedance of maximum flowdischarges using principal components analysis (PCA). In the method we first perform a spatio-temporal cross-correlation analysis between extreme flows data and daily meteorological records for the last 15 days prior to the day of the flood event. We then use PCA to create synthetic variables which are representative of the meteorological variables associated with the flood event (i.e. cumulative rainfall and minimum temperature). Finally, we developed a model to explain the probability of exceedance using the principal components. The methodology was applied to a basin in the foothill area of Santiago, Chile, for which all the extreme events between 1970 and 2013 were analyzed.Results show that elevation rather than distance or location within the contributing basin is what mainly explains the statistical correlation between meteorologicalrecords and flood events. Two principal components were found that explain more than 90% of the total variance of the accumulated rainfalls and minimum temperatures. One component was formed with cumulative rainfall from 3 to 15 days prior to the event, whereas the other one was formed with the minimum temperatures for the last 2 days preceding
Arterberry, Martha E.; Bornstein, Marc H.; Haynes, O. Maurice
2012-01-01
Two analytical procedures for identifying young children as categorizers, the Monte Carlo Simulation and the Probability Estimate Model, were compared. Using a sequential touching method, children age 12, 18, 24, and 30 months were given seven object sets representing different levels of categorical classification. From their touching performance, the probability that children were categorizing was then determined independently using Monte Carlo Simulation and the Probability Estimate Model. The two analytical procedures resulted in different percentages of children being classified as categorizers. Results using the Monte Carlo Simulation were more consistent with group-level analyses than results using the Probability Estimate Model. These findings recommend using the Monte Carlo Simulation for determining individual categorizer classification. PMID:21402410
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.
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
2015-05-01
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 (ARIs) 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
Over, Thomas; Saito, Riki J.; Veilleux, Andrea; Sharpe, Jennifer B.; Soong, David; Ishii, Audrey
2016-01-01
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
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
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). PMID:26709414
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.
A New Approach to Estimating the Probability for β-delayed Neutron Emission
McCutchan, E.A.; Sonzogni, A.A.; Johnson, T.D.; Abriola, D.; Birch, M.; Singh, B.
2014-06-15
The probability for neutron emission following β decay, Pn, is a crucial property for a wide range of physics and applications including nuclear structure, r-process nucleosynthesis, the control of nuclear reactors, and the post-processing of nuclear fuel. Despite much experimental effort, knowledge of Pn values is still lacking in very neutron-rich nuclei, requiring predictions from either systematics or theoretical models. Traditionally, systematic predictions were made by investigating the Pn value as a function of the decay Q value and the neutron separation energy in the daughter nucleus. A new approach to Pn systematics is presented which incorporates the half-life of the decay and the Q value for β-delayed neutron emission. This prescription correlates the known data better, and thus improves the estimation of Pn values for neutron-rich nuclei. Such an approach can be applied to generate input values for r-process network calculations or in the modeling of advanced fuel cycles.
Neumann, Anke; Billionnet, Cécile
2016-06-01
In observational studies without random assignment of the treatment, the unadjusted comparison between treatment groups may be misleading due to confounding. One method to adjust for measured confounders is inverse probability of treatment weighting. This method can also be used in the analysis of time to event data with competing risks. Competing risks arise if for some individuals the event of interest is precluded by a different type of event occurring before, or if only the earliest of several times to event, corresponding to different event types, is observed or is of interest. In the presence of competing risks, time to event data are often characterized by cumulative incidence functions, one for each event type of interest. We describe the use of inverse probability of treatment weighting to create adjusted cumulative incidence functions. This method is equivalent to direct standardization when the weight model is saturated. No assumptions about the form of the cumulative incidence functions are required. The method allows studying associations between treatment and the different types of event under study, while focusing on the earliest event only. We present a SAS macro implementing this method and we provide a worked example. PMID:27084321
Peers Increase Adolescent Risk Taking Even When the Probabilities of Negative Outcomes Are Known
Smith, Ashley R.; Chein, Jason; Steinberg, Laurence
2015-01-01
The majority of adolescent risk taking occurs in the presence of peers, and recent research suggests that the presence of peers may alter how the potential rewards and costs of a decision are valuated or perceived. The current study further explores this notion by investigating how peer observation affects adolescent risk taking when the information necessary to make an informed decision is explicitly provided. We used a novel probabilistic gambling task in which participants decided whether to play or pass on a series of offers for which the reward and loss outcome probabilities were made explicit. Adolescent participants completed the task either alone or under the belief that they were being observed by an unknown peer in a neighboring room. Participants who believed a peer was observing them chose to gamble more often than participants who completed the task alone, and this effect was most evident for decisions with a greater probability of loss. These results suggest that the presence of peers can increase risk taking among adolescents even when specific information regarding the likelihood of positive and negative outcomes is provided. The findings expand our understanding of how peers influence adolescent decision making and have important implications regarding the value of educational programs aimed at reducing risky behaviors during adolescence. PMID:24447118
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
Joseph, Pawlin Vasanthi; Balan, Brindha; Rajendran, Vidhyalakshmi; Prashanthi, Devi Marimuthu; Somnathan, Balasubramanian
2015-01-01
Background: Maps show well the spatial configuration of information. Considerable effort is devoted to the development of geographical information systems (GIS) that increase understanding of public health problems and in particular to collaborate efforts among clinicians, epidemiologists, ecologists, and geographers to map and forecast disease risk. Objectives: Small populations tend to give rise to the most extreme disease rates, even if the actual rates are similar across the areas. Such situations will follow the decision-maker's attention on these areas when they scrutinize the map for decision making or resource allocation. As an alternative, maps can be prepared using P-values (probabilistic values). Materials and Methods: The statistical significance of rates rather than the rates themselves are used to map the results. The incidence rates calculated for each village from 2000 to 2009 is used to estimate λ, the expected number of cases in the study area. The obtained results are mapped using Arc GIS 10.0. Results: The likelihood of infections from low to high is depicted in the map and it is observed that five villages namely, Odanthurai, Coimbatore Corporation, Ikkaraiboluvampatti, Puliakulam, and Pollachi Corporation are more likely to have significantly high incidences. Conclusion: In the probability map, some of the areas with exceptionally high or low rates disappear. These are typically small unpopulated areas, whose rates are unstable due to the small numbers problem. The probability map shows more specific regions of relative risks and expected outcomes. PMID:26170544
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.
Survivorship models for estimating the risk of decompression sickness.
Kumar, K V; Powell, M R
1994-07-01
Several approaches have been used for modeling the incidence of decompression sickness (DCS) such as Hill's dose-response and logistic regression. Most of these methods do not include the time-to-onset information in the model. Survival analysis (failure time analysis) is appropriate when the time to onset of an event is of interest. The applicability of survival analysis for modeling the risk of DCS is illustrated by using data obtained from hypobaric chamber exposures simulating extravehicular activities (n = 426). Univariate analysis of incidence-free survival proportions were obtained for Doppler-detectable circulating microbubbles (CMB), symptoms of DCS and test aborts. A log-linear failure time regression model with 360-min half-time tissue ratio (TR) as covariate was constructed, and estimated probabilities for various TR values were calculated. Further regression analysis by including CMB status in this model showed significant improvement (p < 0.05) in the estimation of DCS over the previous model. Since DCS is dependent on the exposure pressure as well as the duration of exposure, we recommend the use of survival analysis for modeling the risk of DCS. PMID:7945136
de Uña-Álvarez, Jacobo; Meira-Machado, Luís
2015-06-01
Multi-state models are often used for modeling complex event history data. In these models the estimation of the transition probabilities is of particular interest, since they allow for long-term predictions of the process. These quantities have been traditionally estimated by the Aalen-Johansen estimator, which is consistent if the process is Markov. Several non-Markov estimators have been proposed in the recent literature, and their superiority with respect to the Aalen-Johansen estimator has been proved in situations in which the Markov condition is strongly violated. However, the existing estimators have the drawback of requiring that the support of the censoring distribution contains the support of the lifetime distribution, which is not often the case. In this article, we propose two new methods for estimating the transition probabilities in the progressive illness-death model. Some asymptotic results are derived. The proposed estimators are consistent regardless the Markov condition and the referred assumption about the censoring support. We explore the finite sample behavior of the estimators through simulations. The main conclusion of this piece of research is that the proposed estimators are much more efficient than the existing non-Markov estimators in most cases. An application to a clinical trial on colon cancer is included. Extensions to progressive processes beyond the three-state illness-death model are discussed. PMID:25735883