Bayesian Inference for Probabilistic Risk Assessment

Bayesian Inference for Probabilistic Risk Assessment
Author :
Publisher : Springer Science & Business Media
Total Pages : 230
Release :
ISBN-10 : 9781849961875
ISBN-13 : 1849961875
Rating : 4/5 (875 Downloads)

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.


Bayesian Inference for Probabilistic Risk Assessment Related Books

Bayesian Inference for Probabilistic Risk Assessment
Language: en
Pages: 230
Authors: Dana Kelly
Categories: Technology & Engineering
Type: BOOK - Published: 2011-08-30 - Publisher: Springer Science & Business Media

GET EBOOK

Bayesian Inference for Probabilistic Risk Assessment provides a Bayesian foundation for framing probabilistic problems and performing inference on these problem
Probabilistic Risk Analysis
Language: en
Pages: 228
Authors: Tim Bedford
Categories: Mathematics
Type: BOOK - Published: 2001-04-30 - Publisher: Cambridge University Press

GET EBOOK

Probabilistic risk analysis aims to quantify the risk caused by high technology installations. Increasingly, such analyses are being applied to a wider class of
Probability and Risk Analysis
Language: en
Pages: 287
Authors: Igor Rychlik
Categories: Mathematics
Type: BOOK - Published: 2006-10-07 - Publisher: Springer Science & Business Media

GET EBOOK

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 engine
Risk Assessment and Decision Analysis with Bayesian Networks
Language: en
Pages: 527
Authors: Norman Fenton
Categories: Business & Economics
Type: BOOK - Published: 2012-11-07 - Publisher: CRC Press

GET EBOOK

Although many Bayesian Network (BN) applications are now in everyday use, BNs have not yet achieved mainstream penetration. Focusing on practical real-world pro
Risk Assessment and Decision Analysis with Bayesian Networks
Language: en
Pages: 661
Authors: Norman Fenton
Categories: Mathematics
Type: BOOK - Published: 2018-09-03 - Publisher: CRC Press

GET EBOOK

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 editio