Bayesian Methods In Reliability(1st Edition)

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Book Price $59.07 : 1. Introduction To Bayesian Methods In Reliability.- 1. Why Bayesian Methods?.- 1.1 Sparse Data.- 1.2 Decision Problems.- 2. Bayes' Theorem.- 3. Examples From A Safety Study On Gas Transmission Pipelines.- 3.1 Estimating The Probability Of The Development Of A Big Hole.- 3.2 Estimating The Leak Rate Of A Gas Transmission Pipeline.- 4. Conclusions.- References.- 2. An Overview Of The Bayesian Approach.- 1. Background.- 2. Probability Concepts.- 3. Notation.- 4. Reliability Concepts And Models.- 5. Forms Of Data.- 6. Statistical Problems.- 7. Review Of Non-Bayesian Statistical Methods.- 8. Desiderata For Decision-Oriented Statistical Methodology.- 9. Decision-Making.- 10. Degrees Of Belief As Probabilities.- 11. Bayesian Statistical Philosophy.- 12. A Simple Illustration Of Bayesian Learning.- 13. Bayesian Approaches To Typical Statistical Questions.- 14. Assessment Of Prior Densities.- 15. Bayesian Inference For Some Univariate Probability Models.- 16. Approximate Analysis Under Great Prior Uncertainty.- 17. Problems Involving Many Parameters: Empirical Bayes.- 18. Numerical Methods For Practical Bayesian Statistics.- References.- 3. Reliability Modelling And Estimation.- 1. Non-Repairable Systems.- 1.1 Introduction.- 1.2 Describing Reliability.- 1.3 Failure Time Distributions.- 2. Estimation.- 2.1 Introduction.- 2.2 Classical Methods.- 2.3 Bayesian Methods.- 3. Reliability Estimation.- 3.1 Introduction.- 3.2 Binomial Sampling.- 3.3 Pascal Sampling.- 3.4 Poisson Sampling.- 3.5 Hazard Rate Estimation.- References.- 4. Repairable Systems And Growth Models.- 1. Introduction.- 2. Good As New: The Renewal Process.- 3. Estimation.- 4. The Poisson Process.- 5. Bad As Old: The Non-Homogeneous Poisson Process.- 6. Classical Estimation.- 7. Exploratory Analysis.- 8. The Duane Model.- 9. Bayesian Analysis.- References.- 5. The Use Of Expert Judgement In Risk Assessment.- 1. Introduction.- 2. Independence Preservation.- 3. The Quality Of Experts' Judgement.- 4. Calibration Sets And Seed Variables.- 5. A Classical Model.- 6. Bayesian Models.- 7. Some Experimental Results.- References.- 6. Forecasting Software Reliability.- 1. Introduction.- 2. The Software Reliability Growth Problem.- 3. Some Software Reliability Growth Models.- 3.1 Jelinski And Moranda (JM).- 3.2 Bayesian Jelinski-Moranda (BJM).- 3.3 Littlewood (L).- 3.4 Littlewood And Verrall (LV).- 3.5 Keiller And Littlewood (KL).- 3.6 Weibull Order Statistics (W).- 3.7 Duane (D).- 3.8 Goel-Okumoto (GO).- 3.9 Littlewood NHPP (LNHPP).- 4. Examples Of Use.- 5. Analysis Of Predictive Quality.- 5.1 The U-plot.- 5.2 The Y-plot, And Scatter Plot Of U's.- 5.3 Measures Of 'noise'.- 5.3.1 Braun Statistic.- 5.3.2 Median Variability.- 5.3.3 Rate Variability.- 5.4 Prequential Likelihood.- 6. Examples Of Predictive Analysis.- 7. Adapting And Combining Predictions; Future Directions.- 8 Summary And Conclusions.- Acknowledgements.- References.- References.- Author Index. See more