Statistical analysis of reliability data /
"Written for those who have taken a first course in statistical methods, this book takes a modern, computer-oriented approach to describe the statistical techniques used for the assessment of reliability."--Provided by publisher.
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| Format: | eBook |
| Language: | English |
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Boca Raton, Florida :
Chapman and Hall,
1991.
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| Online Access: | View fulltext via EzAccess |
Table of Contents:
- Cover; Half Title; Title Page; Copyright Page; Table of Contents; Preface; 1: Statistical concepts in reliability; 1.1 Introduction; 1.2 Reliability data; 1.3 Repairable and nonrepairable systems; 1.4 Component reliability and system reliability; 1.5 The Binomial and Hypergeometric distributions; 1.6 The Poisson process; 1.7 The reliability literature; 2: Probability distributions in reliability; 2.1 Introduction; 2.2 Preliminaries on life distributions; 2.3 The exponential distribution; 2.4 The Weibull and Gumbel distributions; 2.5 The normal and lognormal distributions
- 2.6 The gamma distribution2.7 Some other lifetime distributions; 2.8 Censored data; 2.9 Simple data analytic methods: no censoring; 2.10 Data analytic methods: type II censoring; 2.11 Data analytic methods: general censoring; 3: Statistical methods for single samples; 3.1 Introduction; 3.2 Maximum likelihood estimation: generalities; 3.3 Maximum likelihood estimation: illustrations; 3.4 Tests and confidence regions based on likelihood; 3.5 Remarks on likelihood-based methods; 3.6 Goodness-of-fit; 4: Regression models for reliability data; 4.1 Introduction; 4.2 Acx:elerated life models
- 4.3 Proportional hazards models4.4 Proportional odds models; 4.5 Generalizations; 4.6 An argument from fracture mechanics; 4.7 Models based on the Weibull distribution; 4.8 An example: breaking strengths of carbon fibres and bundles; 4.9 Other examples of comparing several samples; 4.10 Weibull ANOVA; 4.11 Buffonâ#x80;#x99;s beams: an historical example of reliability data; 4.12 Concluding remarks; 5: Proportional hazards modelling; 5.1 Introduction; 5.2 Analysis of the semiparametric PH model; 5.3 Estimation of the survivor and hazard functions; 5.4 Model checking; 5.5 Numerical examples
- 6: The Bayesian approach6.1 Introduction; 6.2 A review of the Bayesian approach to statistics; 6.3 Elements of Bayesian statistics; 6.4 Further topics in Bayesian inference; 6.5 Decision analysis; 6.6 Bayesian analysis of reliability data; 7: Multivariate models; 7.1 Preliminaries; 7.2 Some multivariate failure time distributions; 7.3 Complete observation of T; 7.4 Competing risks; 8: Repairable systems; 8.1 Introduction; 8.2 Framework; 8.3 ROCOF; 8.4 Simple statistical methods; 8.5 Non-homogeneous Poisson process models; 8.6 NHPP with log-linear ROCOF; 8.7 NHPP with ROCOF V2
- 8.8 Choice of NHPP model8.9 Discussion; 9: Models for system reliability; 9.1 Introduction; 9.2 Coherent systems; 9.3 Estimation of reliability for coherent systems; 9.4 Multi-state reliability theory; 9.5 Load-sharing systems: the Daniels model; 9.6 Extensions of the Daniels model; 9.7 Time to failure; 9.8 A more general model; 9.9 Local load-sharing; 9.10 Exact calculations; 9.11 Approximations for local load-sharing systems; 9.12 Statistical applications of load-sharing models; Appendix: The Delta method; References; Author index