Bayesian Methods in Reliability
Editat de P. Sander, R. Badouxen Limba Engleză Hardback – 30 sep 1991
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Specificații
ISBN-13: 9780792314141
ISBN-10: 079231414X
Pagini: 236
Dimensiuni: 160 x 241 x 19 mm
Greutate: 0.52 kg
Editura: Springer
Locul publicării:Dordrecht, Netherlands
ISBN-10: 079231414X
Pagini: 236
Dimensiuni: 160 x 241 x 19 mm
Greutate: 0.52 kg
Editura: Springer
Locul publicării:Dordrecht, Netherlands
Public țintă
ResearchCuprins
1. Introduction to Bayesian Methods in Reliability.- 1. Why Bayesian Methods?.- 2. Bayes’ Theorem.- 3. Examples from a Safety Study on Gas transmission Pipelines.- 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.- 2. Estimation.- 3. Reliability 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 SoftwareReliability Growth Models.- 4. Examples of Use.- 5. Analysis of Predictive Quality.- 6. Examples of Predictive Analysis.- 7. Adapting and Combining Predictions; Future Directions.- 8 Summary and Conclusions.- Acknowledgements.- References.- References.- Author index.