Bayesian Inference For Probabilistic Risk Assessment

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Bayesian Inference for Probabilistic Risk Assessment

Dana Kelly,Curtis Smith
Bayesian Inference for Probabilistic Risk Assessment Book PDF

Author : Dana Kelly,Curtis Smith
Publisher : Springer Science & Business Media
Page : 230 pages
File Size : 40,7 Mb
Release : 2011-08-30
Category : Technology & Engineering
ISBN : 9781849961875

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Bayesian Inference for Probabilistic Risk Assessment by Dana Kelly,Curtis Smith Pdf

Bayesian Inference for Probabilistic Risk Assessment provides a Bayesian foundation for framing probabilistic problems and performing inference on these problems. Inference in the book employs a modern computational approach known as Markov chain Monte Carlo (MCMC). The MCMC approach may be implemented using custom-written routines or existing general purpose commercial or open-source software. This book uses an open-source program called OpenBUGS (commonly referred to as WinBUGS) to solve the inference problems that are described. A powerful feature of OpenBUGS is its automatic selection of an appropriate MCMC sampling scheme for a given problem. The authors provide analysis “building blocks” that can be modified, combined, or used as-is to solve a variety of challenging problems. The MCMC approach used is implemented via textual scripts similar to a macro-type programming language. Accompanying most scripts is a graphical Bayesian network illustrating the elements of the script and the overall inference problem being solved. Bayesian Inference for Probabilistic Risk Assessment also covers the important topics of MCMC convergence and Bayesian model checking. Bayesian Inference for Probabilistic Risk Assessment is aimed at scientists and engineers who perform or review risk analyses. It provides an analytical structure for combining data and information from various sources to generate estimates of the parameters of uncertainty distributions used in risk and reliability models.

Probabilistic Risk Analysis

Tim Bedford,Roger Cooke
Probabilistic Risk Analysis Book PDF

Author : Tim Bedford,Roger Cooke
Publisher : Cambridge University Press
Page : 228 pages
File Size : 52,6 Mb
Release : 2001-04-30
Category : Mathematics
ISBN : 0521773202

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Probabilistic Risk Analysis by Tim Bedford,Roger Cooke Pdf

A graduate level textbook on probabilistic risk analysis, aimed at statisticians, operations researchers and engineers.

Probabilistic Risk Analysis and Bayesian Decision Theory

Marcel van Oijen,Mark Brewer
Probabilistic Risk Analysis and Bayesian Decision Theory Book PDF

Author : Marcel van Oijen,Mark Brewer
Publisher : Springer Nature
Page : 118 pages
File Size : 41,7 Mb
Release : 2022-11-23
Category : Mathematics
ISBN : 9783031163333

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Probabilistic Risk Analysis and Bayesian Decision Theory by Marcel van Oijen,Mark Brewer Pdf

The book shows how risk, defined as the statistical expectation of loss, can be formally decomposed as the product of two terms: hazard probability and system vulnerability. This requires a specific definition of vulnerability that replaces the many fuzzy definitions abounding in the literature. The approach is expanded to more complex risk analysis with three components rather than two, and with various definitions of hazard. Equations are derived to quantify the uncertainty of each risk component and show how the approach relates to Bayesian decision theory. Intended for statisticians, environmental scientists and risk analysts interested in the theory and application of risk analysis, this book provides precise definitions, new theory, and many examples with full computer code. The approach is based on straightforward use of probability theory which brings rigour and clarity. Only a moderate knowledge and understanding of probability theory is expected from the reader.

Risk Assessment and Decision Analysis with Bayesian Networks

Norman Fenton,Martin Neil
Risk Assessment and Decision Analysis with Bayesian Networks Book PDF

Author : Norman Fenton,Martin Neil
Publisher : CRC Press
Page : 638 pages
File Size : 40,9 Mb
Release : 2018-09-03
Category : Mathematics
ISBN : 9781351978972

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Risk Assessment and Decision Analysis with Bayesian Networks by Norman Fenton,Martin Neil Pdf

Since the first edition of this book published, Bayesian networks have become even more important for applications in a vast array of fields. This second edition includes new material on influence diagrams, learning from data, value of information, cybersecurity, debunking bad statistics, and much more. Focusing on practical real-world problem-solving and model building, as opposed to algorithms and theory, it explains how to incorporate knowledge with data to develop and use (Bayesian) causal models of risk that provide more powerful insights and better decision making than is possible from purely data-driven solutions. Features Provides all tools necessary to build and run realistic Bayesian network models Supplies extensive example models based on real risk assessment problems in a wide range of application domains provided; for example, finance, safety, systems reliability, law, forensics, cybersecurity and more Introduces all necessary mathematics, probability, and statistics as needed Establishes the basics of probability, risk, and building and using Bayesian network models, before going into the detailed applications A dedicated website contains exercises and worked solutions for all chapters along with numerous other resources. The AgenaRisk software contains a model library with executable versions of all of the models in the book. Lecture slides are freely available to accredited academic teachers adopting the book on their course.

Risk Analysis in Engineering

Mohammad Modarres
Risk Analysis in Engineering Book PDF

Author : Mohammad Modarres
Publisher : CRC Press
Page : 408 pages
File Size : 53,6 Mb
Release : 2016-04-27
Category : Mathematics
ISBN : 9781420003499

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Risk Analysis in Engineering by Mohammad Modarres Pdf

Based on the author's 20 years of teaching, Risk Analysis in Engineering: Techniques, Tools, and Trends presents an engineering approach to probabilistic risk analysis (PRA). It emphasizes methods for comprehensive PRA studies, including techniques for risk management. The author assumes little or no prior knowledge of risk analysis on the p

Risk Assessment and Decision Analysis with Bayesian Networks

Norman Fenton,Martin Neil
Risk Assessment and Decision Analysis with Bayesian Networks Book PDF

Author : Norman Fenton,Martin Neil
Publisher : CRC Press
Page : 516 pages
File Size : 46,7 Mb
Release : 2012-11-07
Category : Business & Economics
ISBN : 9781439809112

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Risk Assessment and Decision Analysis with Bayesian Networks by Norman Fenton,Martin Neil Pdf

Although many Bayesian Network (BN) applications are now in everyday use, BNs have not yet achieved mainstream penetration. Focusing on practical real-world problem solving and model building, as opposed to algorithms and theory, Risk Assessment and Decision Analysis with Bayesian Networks explains how to incorporate knowledge with data to develop and use (Bayesian) causal models of risk that provide powerful insights and better decision making. Provides all tools necessary to build and run realistic Bayesian network models Supplies extensive example models based on real risk assessment problems in a wide range of application domains provided; for example, finance, safety, systems reliability, law, and more Introduces all necessary mathematics, probability, and statistics as needed The book first establishes the basics of probability, risk, and building and using BN models, then goes into the detailed applications. The underlying BN algorithms appear in appendices rather than the main text since there is no need to understand them to build and use BN models. Keeping the body of the text free of intimidating mathematics, the book provides pragmatic advice about model building to ensure models are built efficiently. A dedicated website, www.BayesianRisk.com, contains executable versions of all of the models described, exercises and worked solutions for all chapters, PowerPoint slides, numerous other resources, and a free downloadable copy of the AgenaRisk software.

Probability and Bayesian Statistics

R. Viertl
Probability and Bayesian Statistics Book PDF

Author : R. Viertl
Publisher : Springer Science & Business Media
Page : 505 pages
File Size : 43,8 Mb
Release : 2012-12-06
Category : Mathematics
ISBN : 9781461318859

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Probability and Bayesian Statistics by R. Viertl Pdf

This book contains selected and refereed contributions to the "Inter national Symposium on Probability and Bayesian Statistics" which was orga nized to celebrate the 80th birthday of Professor Bruno de Finetti at his birthplace Innsbruck in Austria. Since Professor de Finetti died in 1985 the symposium was dedicated to the memory of Bruno de Finetti and took place at Igls near Innsbruck from 23 to 26 September 1986. Some of the pa pers are published especially by the relationship to Bruno de Finetti's scientific work. The evolution of stochastics shows growing importance of probability as coherent assessment of numerical values as degrees of believe in certain events. This is the basis for Bayesian inference in the sense of modern statistics. The contributions in this volume cover a broad spectrum ranging from foundations of probability across psychological aspects of formulating sub jective probability statements, abstract measure theoretical considerations, contributions to theoretical statistics and stochastic processes, to real applications in economics, reliability and hydrology. Also the question is raised if it is necessary to develop new techniques to model and analyze fuzzy observations in samples. The articles are arranged in alphabetical order according to the family name of the first author of each paper to avoid a hierarchical ordering of importance of the different topics. Readers interested in special topics can use the index at the end of the book as guide.

Probability and Risk Analysis

Igor Rychlik,Jesper Rydén
Probability and Risk Analysis Book PDF

Author : Igor Rychlik,Jesper Rydén
Publisher : Springer Science & Business Media
Page : 281 pages
File Size : 41,5 Mb
Release : 2006-10-07
Category : Mathematics
ISBN : 9783540395218

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Probability and Risk Analysis by Igor Rychlik,Jesper Rydén Pdf

This text presents notions and ideas at the foundations of a statistical treatment of risks. The focus is on statistical applications within the field of engineering risk and safety analysis. Coverage includes Bayesian methods. Such knowledge facilitates the understanding of the influence of random phenomena and gives a deeper understanding of the role of probability in risk analysis. The text is written for students who have studied elementary undergraduate courses in engineering mathematics, perhaps including a minor course in statistics. This book differs from typical textbooks in its verbal approach to many explanations and examples.

Uncertainty in Risk Assessment

Terje Aven,Piero Baraldi,Roger Flage,Enrico Zio
Uncertainty in Risk Assessment Book PDF

Author : Terje Aven,Piero Baraldi,Roger Flage,Enrico Zio
Publisher : John Wiley & Sons
Page : 152 pages
File Size : 42,7 Mb
Release : 2013-12-17
Category : Mathematics
ISBN : 9781118763063

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Uncertainty in Risk Assessment by Terje Aven,Piero Baraldi,Roger Flage,Enrico Zio Pdf

Explores methods for the representation and treatment of uncertainty in risk assessment In providing guidance for practical decision-making situations concerning high-consequence technologies (e.g., nuclear, oil and gas, transport, etc.), the theories and methods studied in Uncertainty in Risk Assessment have wide-ranging applications from engineering and medicine to environmental impacts and natural disasters, security, and financial risk management. The main focus, however, is on engineering applications. While requiring some fundamental background in risk assessment, as well as a basic knowledge of probability theory and statistics, Uncertainty in Risk Assessment can be read profitably by a broad audience of professionals in the field, including researchers and graduate students on courses within risk analysis, statistics, engineering, and the physical sciences. Uncertainty in Risk Assessment: Illustrates the need for seeing beyond probability to represent uncertainties in risk assessment contexts. Provides simple explanations (supported by straightforward numerical examples) of the meaning of different types of probabilities, including interval probabilities, and the fundamentals of possibility theory and evidence theory. Offers guidance on when to use probability and when to use an alternative representation of uncertainty. Presents and discusses methods for the representation and characterization of uncertainty in risk assessment. Uses examples to clearly illustrate ideas and concepts.

Bayesian Data Analysis, Third Edition

Andrew Gelman,John B. Carlin,Hal S. Stern,David B. Dunson,Aki Vehtari,Donald B. Rubin
Bayesian Data Analysis Third Edition Book PDF

Author : Andrew Gelman,John B. Carlin,Hal S. Stern,David B. Dunson,Aki Vehtari,Donald B. Rubin
Publisher : CRC Press
Page : 677 pages
File Size : 54,8 Mb
Release : 2013-11-01
Category : Mathematics
ISBN : 9781439840955

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Bayesian Data Analysis, Third Edition by Andrew Gelman,John B. Carlin,Hal S. Stern,David B. Dunson,Aki Vehtari,Donald B. Rubin Pdf

Now in its third edition, this classic book is widely considered the leading text on Bayesian methods, lauded for its accessible, practical approach to analyzing data and solving research problems. Bayesian Data Analysis, Third Edition continues to take an applied approach to analysis using up-to-date Bayesian methods. The authors—all leaders in the statistics community—introduce basic concepts from a data-analytic perspective before presenting advanced methods. Throughout the text, numerous worked examples drawn from real applications and research emphasize the use of Bayesian inference in practice. New to the Third Edition Four new chapters on nonparametric modeling Coverage of weakly informative priors and boundary-avoiding priors Updated discussion of cross-validation and predictive information criteria Improved convergence monitoring and effective sample size calculations for iterative simulation Presentations of Hamiltonian Monte Carlo, variational Bayes, and expectation propagation New and revised software code The book can be used in three different ways. For undergraduate students, it introduces Bayesian inference starting from first principles. For graduate students, the text presents effective current approaches to Bayesian modeling and computation in statistics and related fields. For researchers, it provides an assortment of Bayesian methods in applied statistics. Additional materials, including data sets used in the examples, solutions to selected exercises, and software instructions, are available on the book’s web page.

Bayesian Inference for Stochastic Processes

Lyle D. Broemeling
Bayesian Inference for Stochastic Processes Book PDF

Author : Lyle D. Broemeling
Publisher : CRC Press
Page : 373 pages
File Size : 44,7 Mb
Release : 2017-12-12
Category : Mathematics
ISBN : 9781315303574

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Bayesian Inference for Stochastic Processes by Lyle D. Broemeling Pdf

This is the first book designed to introduce Bayesian inference procedures for stochastic processes. There are clear advantages to the Bayesian approach (including the optimal use of prior information). Initially, the book begins with a brief review of Bayesian inference and uses many examples relevant to the analysis of stochastic processes, including the four major types, namely those with discrete time and discrete state space and continuous time and continuous state space. The elements necessary to understanding stochastic processes are then introduced, followed by chapters devoted to the Bayesian analysis of such processes. It is important that a chapter devoted to the fundamental concepts in stochastic processes is included. Bayesian inference (estimation, testing hypotheses, and prediction) for discrete time Markov chains, for Markov jump processes, for normal processes (e.g. Brownian motion and the Ornstein–Uhlenbeck process), for traditional time series, and, lastly, for point and spatial processes are described in detail. Heavy emphasis is placed on many examples taken from biology and other scientific disciplines. In order analyses of stochastic processes, it will use R and WinBUGS. Features: Uses the Bayesian approach to make statistical Inferences about stochastic processes The R package is used to simulate realizations from different types of processes Based on realizations from stochastic processes, the WinBUGS package will provide the Bayesian analysis (estimation, testing hypotheses, and prediction) for the unknown parameters of stochastic processes To illustrate the Bayesian inference, many examples taken from biology, economics, and astronomy will reinforce the basic concepts of the subject A practical approach is implemented by considering realistic examples of interest to the scientific community WinBUGS and R code are provided in the text, allowing the reader to easily verify the results of the inferential procedures found in the many examples of the book Readers with a good background in two areas, probability theory and statistical inference, should be able to master the essential ideas of this book.

Computational Methods for Reliability and Risk Analysis

Enrico Zio
Computational Methods for Reliability and Risk Analysis Book PDF

Author : Enrico Zio
Publisher : World Scientific Publishing Company
Page : 364 pages
File Size : 45,5 Mb
Release : 2009-01-22
Category : Technology & Engineering
ISBN : 9789813107427

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Computational Methods for Reliability and Risk Analysis by Enrico Zio Pdf

This book illustrates a number of modelling and computational techniques for addressing relevant issues in reliability and risk analysis. In particular, it provides: i) a basic illustration of some methods used in reliability and risk analysis for modelling the stochastic failure and repair behaviour of systems, e.g. the Markov and Monte Carlo simulation methods; ii) an introduction to Genetic Algorithms, tailored to their application for RAMS (Reliability, Availability, Maintainability and Safety) optimization; iii) an introduction to key issues of system reliability and risk analysis, like dependent failures and importance measures; and iv) a presentation of the issue of uncertainty and of the techniques of sensitivity and uncertainty analysis used in support of reliability and risk analysis. The book provides a technical basis for senior undergraduate or graduate courses and a reference for researchers and practitioners in the field of reliability and risk analysis. Several practical examples are included to demonstrate the application of the concepts and techniques in practice. This book is also available as a set with An Introduction to the Basics of Reliability and Risk Analysis and Basics of Reliability and Risk Analysis. Foreword Foreword (64k) Sample Chapter(s) Chapter 1: Markov Reliability and Availability Analysis (1,181k) Request Inspection Copy

Reliability and Risk

Nozer D. Singpurwalla
Reliability and Risk Book PDF

Author : Nozer D. Singpurwalla
Publisher : John Wiley & Sons
Page : 396 pages
File Size : 51,7 Mb
Release : 2006-08-14
Category : Mathematics
ISBN : 9780470060339

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Reliability and Risk by Nozer D. Singpurwalla Pdf

We all like to know how reliable and how risky certain situations are, and our increasing reliance on technology has led to the need for more precise assessments than ever before. Such precision has resulted in efforts both to sharpen the notions of risk and reliability, and to quantify them. Quantification is required for normative decision-making, especially decisions pertaining to our safety and wellbeing. Increasingly in recent years Bayesian methods have become key to such quantifications. Reliability and Risk provides a comprehensive overview of the mathematical and statistical aspects of risk and reliability analysis, from a Bayesian perspective. This book sets out to change the way in which we think about reliability and survival analysis by casting them in the broader context of decision-making. This is achieved by: Providing a broad coverage of the diverse aspects of reliability, including: multivariate failure models, dynamic reliability, event history analysis, non-parametric Bayes, competing risks, co-operative and competing systems, and signature analysis. Covering the essentials of Bayesian statistics and exchangeability, enabling readers who are unfamiliar with Bayesian inference to benefit from the book. Introducing the notion of “composite reliability”, or the collective reliability of a population of items. Discussing the relationship between notions of reliability and survival analysis and econometrics and financial risk. Reliability and Risk can most profitably be used by practitioners and research workers in reliability and survivability as a source of information, reference, and open problems. It can also form the basis of a graduate level course in reliability and risk analysis for students in statistics, biostatistics, engineering (industrial, nuclear, systems), operations research, and other mathematically oriented scientists, wherein the instructor could supplement the material with examples and problems.

Low-Probability High-Consequence Risk Analysis

Ray Waller
Low Probability High Consequence Risk Analysis Book PDF

Author : Ray Waller
Publisher : Springer Science & Business Media
Page : 561 pages
File Size : 41,7 Mb
Release : 2013-11-21
Category : Science
ISBN : 9781475718188

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Low-Probability High-Consequence Risk Analysis by Ray Waller Pdf

In recent years public attention has focused on an array of low-probability/high-consequence (LC/HC) events that pose a signif icant threat to human health, safety, and the environment. At the same time, public and private sector responsibilities for the assessment and management of such events have grown because of a perceived need to anticipate, prevent, or reduce the risks. In attempting to meet these responsibilities, legislative, judicial, regulatory, and private sector institutions have had to deal with the extraordinarily complex problem of assessing and balancing LP/ HC risks against the costs and ben if its of risk reduction. The need to help society cope with LP/HC events such as nuclear power plant accidents, toxic spills, chemical plant explosions, and transportation accidents has given rise to the development of a new intellectual endeavor: LP/HC risk analysis. The scope and complexity of these analyses require a high degree of cooperative effort on the part of specialists from many f~elds. Analyzing technical, social, and value issues requires the efforts of physicists, biologists, geneticists, statisticians, chemists, engineers, political scientists, sociologists, decision analysts, management scientists, economists, psychologists, ethicists, lawyers, and policy analysts. Included in this volume are papers by authors in each of these disciplines. The papers share in common a focus on one or more of the following questions that are generic to the analysis of LP/HC risks.

Foundations of Risk Analysis

Terje Aven
Foundations of Risk Analysis Book PDF

Author : Terje Aven
Publisher : John Wiley & Sons
Page : 245 pages
File Size : 54,6 Mb
Release : 2012-04-09
Category : Mathematics
ISBN : 9781119966975

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Foundations of Risk Analysis by Terje Aven Pdf

Foundations of Risk Analysis presents the issues core to risk analysis – understanding what risk means, expressing risk, building risk models, addressing uncertainty, and applying probability models to real problems. The author provides the readers with the knowledge and basic thinking they require to successfully manage risk and uncertainty to support decision making. This updated edition reflects recent developments on risk and uncertainty concepts, representations and treatment. New material in Foundations of Risk Analysis includes: An up to date presentation of how to understand, define and describe risk based on research carried out in recent years. A new definition of the concept of vulnerability consistent with the understanding of risk. Reflections on the need for seeing beyond probabilities to measure/describe uncertainties. A presentation and discussion of a method for assessing the importance of assumptions (uncertainty factors) in the background knowledge that the subjective probabilities are based on A brief introduction to approaches that produce interval (imprecise) probabilities instead of exact probabilities. In addition the new version provides a number of other improvements, for example, concerning the use of cost-benefit analyses and the As Low As Reasonably Practicable (ALARP) principle. Foundations of Risk Analysis provides a framework for understanding, conducting and using risk analysis suitable for advanced undergraduates, graduates, analysts and researchers from statistics, engineering, finance, medicine and the physical sciences, as well as for managers facing decision making problems involving risk and uncertainty.