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Bayesian Methods in Reliability

  • Book
  • © 1991

Overview

Editors:
  1. P. Sander

    1. TU Eindhoven, The Netherlands

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    You can also search for this editor in PubMed   Google Scholar

  2. R. Badoux

    1. TU Eindhoven, The Netherlands

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    You can also search for this editor in PubMed   Google Scholar

Part of the book series: Topics in Safety, Reliability and Quality (TSRX, volume 1)

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Table of contents (6 chapters)

  1. Front Matter

    Pages i-x
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  2. Introduction to Bayesian Methods in Reliability

    • Robert A. J. Badoux
    Pages 1-13

  3. An Overview of the Bayesian Approach

    • Adrian F. M. Smith
    Pages 15-79

  4. Reliability Modelling and Estimation

    • Martin Newby
    Pages 81-100

  5. Repairable Systems and Growth Models

    • Martin Newby
    Pages 101-117

  6. The Use of Expert Judgement in Risk Assessment

    • Simon French, Roger M. Cooke, Michael P. Wiper
    Pages 119-134

  7. Forecasting Software Reliability

    • Bev Littlewood
    Pages 135-201

  8. Back Matter

    Pages 203-223
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Keywords

About this book

When data is collected on failure or survival a list of times is obtained. Some of the times are failure times and others are the times at which the subject left the experiment. These times both give information about the performance of the system. The two types will be referred to as failure and censoring times (cf. Smith section 5). * A censoring time, t, gives less information than a failure time, for it is * known only that the item survived past t and not when it failed. The data is tn and of censoring thus collected as a list of failure times t , . . . , l * * * times t , t , . . . , t • 1 z m 2. 2. Classical methods The failure times are assumed to follow a parametric distribution F(t;B) with and reliability R(t;B). There are several methods of estimating density f(t;B) the parameter B based only on the data in the sample without any prior assumptions about B. The availability of powerful computers and software packages has made the method of maximum likelihood the most popular. Descriptions of most methods can be found in the book by Mann, Schafer and Singpurwalla (1974). In general the method of maximum likelihood is the most useful of the classical approaches. The likelihood approach is based on constructing the joint probability distrilmtion or density for a sample.

Editors and Affiliations

  • TU Eindhoven, The Netherlands

    P. Sander, R. Badoux

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