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Practical applications of Bayesian reliability

Basic concepts of Bayesian statistics, models, reasons, and theory are presented in the following chapter. Coverage of Bayesian computation, Metropolis-Hastings algorithm, and Gibbs Sampling comes next.

Bibliographic Details
Main Authors: Liu, Yan, Abeyratne, Athula I. (Author)
Format: eBook
Language:English
Published: Hoboken, NJ Wiley 2019
Subjects:
Reliability (engineering) / Statistical Methods / Fast
Mathematics / Applied / Bisacsh
Bayesian Statistical Decision Theory / Http://id.loc.gov/authorities/subjects/sh85012506
Mathematics / Probability & Statistics / General / Bisacsh
Bayesian Statistical Decision Theory / Fast
Théorie De La Décision Bayésienne
Reliability (engineering) / Statistical Methods / Http://id.loc.gov/authorities/subjects/sh85112512
Online Access:
Collection: O'Reilly - Collection details see MPG.ReNa
Table of Contents:
  • Basic Concepts of Reliability Engineering
  • Basic Concepts of Bayesian Statistics and Models
  • Bayesian Computation
  • Reliability Distributions (Bayesian Perspective)
  • Reliability Demonstration Testing
  • Capability and Design for Reliability
  • System Reliability Bayesian Model
  • Bayesian Hierarchical Model
  • Regression Models
  • Appendix A Guidance for Installing R, R Studio, JAGS, and rjags
  • Appendix B Commonly Used R Commands
  • Appendix C Probability Distributions
  • Appendix D Jeffreys Prior
  • Includes bibliographical references and index

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