Probabilistic Risk Analysis and Bayesian Decision Theory

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Publisher : Springer Nature
ISBN 13 : 3031163338
Total Pages : 118 pages
Book Rating : 4.33/5 ( download)

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Book Synopsis Probabilistic Risk Analysis and Bayesian Decision Theory by : Marcel van Oijen

Download or read book Probabilistic Risk Analysis and Bayesian Decision Theory written by Marcel van Oijen and published by Springer Nature. This book was released on 2022-11-23 with total page 118 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Bayesian Compendium

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Publisher : Springer Nature
ISBN 13 : 3030558975
Total Pages : 209 pages
Book Rating : 4.70/5 ( download)

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Book Synopsis Bayesian Compendium by : Marcel van Oijen

Download or read book Bayesian Compendium written by Marcel van Oijen and published by Springer Nature. This book was released on 2020-09-17 with total page 209 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book describes how Bayesian methods work. Its primary aim is to demystify them, and to show readers: Bayesian thinking isn’t difficult and can be used in virtually every kind of research. In addition to revealing the underlying simplicity of statistical methods, the book explains how to parameterise and compare models while accounting for uncertainties in data, model parameters and model structures. How exactly should data be used in modelling? The literature offers a bewildering variety of techniques and approaches (Bayesian calibration, data assimilation, Kalman filtering, model-data fusion, etc). This book provides a short and easy guide to all of these and more. It was written from a unifying Bayesian perspective, which reveals how the multitude of techniques and approaches are in fact all related to one another. Basic notions from probability theory are introduced. Executable code examples are included to enhance the book’s practical use for scientific modellers, and all code is available online as well.

Risk Assessment and Decision Analysis with Bayesian Networks

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Publisher : CRC Press
ISBN 13 : 1351978969
Total Pages : 672 pages
Book Rating : 4.65/5 ( download)

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Book Synopsis Risk Assessment and Decision Analysis with Bayesian Networks by : Norman Fenton

Download or read book Risk Assessment and Decision Analysis with Bayesian Networks written by Norman Fenton and published by CRC Press. This book was released on 2018-09-03 with total page 672 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Probabilistic Risk Analysis

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Publisher : Cambridge University Press
ISBN 13 : 9780521773201
Total Pages : 228 pages
Book Rating : 4.02/5 ( download)

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Book Synopsis Probabilistic Risk Analysis by : Tim Bedford

Download or read book Probabilistic Risk Analysis written by Tim Bedford and published by Cambridge University Press. This book was released on 2001-04-30 with total page 228 pages. Available in PDF, EPUB and Kindle. Book excerpt: A graduate level textbook on probabilistic risk analysis, aimed at statisticians, operations researchers and engineers.

Statistical Decision Theory and Bayesian Analysis

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Publisher : Springer Science & Business Media
ISBN 13 : 147574286X
Total Pages : 633 pages
Book Rating : 4.62/5 ( download)

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Book Synopsis Statistical Decision Theory and Bayesian Analysis by : James O. Berger

Download or read book Statistical Decision Theory and Bayesian Analysis written by James O. Berger and published by Springer Science & Business Media. This book was released on 2013-03-14 with total page 633 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this new edition the author has added substantial material on Bayesian analysis, including lengthy new sections on such important topics as empirical and hierarchical Bayes analysis, Bayesian calculation, Bayesian communication, and group decision making. With these changes, the book can be used as a self-contained introduction to Bayesian analysis. In addition, much of the decision-theoretic portion of the text was updated, including new sections covering such modern topics as minimax multivariate (Stein) estimation.

Bayesian Inference for Probabilistic Risk Assessment

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Publisher : Springer Science & Business Media
ISBN 13 : 1849961875
Total Pages : 230 pages
Book Rating : 4.75/5 ( download)

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Book Synopsis Bayesian Inference for Probabilistic Risk Assessment by : Dana Kelly

Download or read book Bayesian Inference for Probabilistic Risk Assessment written by Dana Kelly and published by Springer Science & Business Media. This book was released on 2011-08-30 with total page 230 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Decisions under Uncertainty

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Publisher : Cambridge University Press
ISBN 13 : 1316584038
Total Pages : 690 pages
Book Rating : 4.33/5 ( download)

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Book Synopsis Decisions under Uncertainty by : Ian Jordaan

Download or read book Decisions under Uncertainty written by Ian Jordaan and published by Cambridge University Press. This book was released on 2005-04-07 with total page 690 pages. Available in PDF, EPUB and Kindle. Book excerpt: To better understand the core concepts of probability and to see how they affect real-world decisions about design and system performance, engineers and scientists might want to ask themselves the following questions: what exactly is meant by probability? What is the precise definition of the 100-year load and how is it calculated? What is an 'extremal' probability distribution? What is the Bayesian approach? How is utility defined? How do games fit into probability theory? What is entropy? How do I apply these ideas in risk analysis? Starting from the most basic assumptions, this 2005 book develops a coherent theory of probability and broadens it into applications in decision theory, design, and risk analysis. This book is written for engineers and scientists interested in probability and risk. It can be used by undergraduates, graduate students, or practicing engineers.

Statistical Decision Theory and Related Topics V

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Publisher : Springer Science & Business Media
ISBN 13 : 146122618X
Total Pages : 535 pages
Book Rating : 4.85/5 ( download)

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Book Synopsis Statistical Decision Theory and Related Topics V by : Shanti S. Gupta

Download or read book Statistical Decision Theory and Related Topics V written by Shanti S. Gupta and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 535 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Fifth Purdue International Symposium on Statistical Decision The was held at Purdue University during the period of ory and Related Topics June 14-19,1992. The symposium brought together many prominent leaders and younger researchers in statistical decision theory and related areas. The format of the Fifth Symposium was different from the previous symposia in that in addition to the 54 invited papers, there were 81 papers presented in contributed paper sessions. Of the 54 invited papers presented at the sym posium, 42 are collected in this volume. The papers are grouped into a total of six parts: Part 1 - Retrospective on Wald's Decision Theory and Sequential Analysis; Part 2 - Asymptotics and Nonparametrics; Part 3 - Bayesian Analysis; Part 4 - Decision Theory and Selection Procedures; Part 5 - Probability and Probabilistic Structures; and Part 6 - Sequential, Adaptive, and Filtering Problems. While many of the papers in the volume give the latest theoretical developments in these areas, a large number are either applied or creative review papers.

Risk Assessment and Decision Analysis with Bayesian Networks

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Publisher : CRC Press
ISBN 13 : 1439809119
Total Pages : 516 pages
Book Rating : 4.12/5 ( download)

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Book Synopsis Risk Assessment and Decision Analysis with Bayesian Networks by : Norman Fenton

Download or read book Risk Assessment and Decision Analysis with Bayesian Networks written by Norman Fenton and published by CRC Press. This book was released on 2012-11-07 with total page 516 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Uncertainty and Risk

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Publisher : Springer Science & Business Media
ISBN 13 : 3540489355
Total Pages : 299 pages
Book Rating : 4.51/5 ( download)

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Book Synopsis Uncertainty and Risk by : Mohammed Abdellaoui

Download or read book Uncertainty and Risk written by Mohammed Abdellaoui and published by Springer Science & Business Media. This book was released on 2007-08-10 with total page 299 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book tries to sort out the different meanings of uncertainty and to discover their foundations. It shows that uncertainty can be represented using various tools and mental guidelines. Coverage also examines alternative ways to deal with risk and risk attitude concepts. Behavior under uncertainty emerges from this book as something to base more on inquiry and reflection rather than on mere intuition.