BAYESIAN METHODS FOR ASSESSING SYSTEM RELIABILITY: MODELS AND COMPUTATION

Series on Quality, Reliability and Engineering Statistics Vol. 10: Modern Statistical and Mathematical Methods in Reliability

Volumn , Issue , 2005, Pages 41-54

  Graves, Todd L ^a   Hamada, Michael S ^a  

^a LOS ALAMOS NATIONAL LABORATORY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

EID: 34147198138     PISSN: None     EISSN: None     Source Type: Book    
DOI: None     Document Type: Chapter

References (13)

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3. D. V. Mastran and N. D. Singpurwalla, A Bayesian estimation of the reliability of coherent structures, Operations Research 26, 663-672 (1978).
4. B. Natvig and H. Eide, Bayesian estimation of system reliability, Scandznavian Journal of Statistics 14, 319-327 (1987).
5. H. F. Martz, R. A. Waller, and E. T. Fickas, Bayesian reliability analysis of series systems of binomial subsystems and components, Technometrics 30, 6.
6. H. F. Martz and R. A. Waller, Bayesian reliability analysis of complex series/parallei systems of binomial subsystems and components, Technometrics
7. T. Graves, M. Hamada, J. Booker, M. Decroix, C. Bowyer, K. Chilcoat, and S. K. Thompson, Estimating a proportion using stratified data arising from both convenience and random samples, Los Alamos National Laboratory Technical Report LA-UR-03-8396 (2004).
8. V. Johnson, T. Graves, M. Hamada, and C. S. Reese, A hierarchical model for estimating the reliability of complex systems (with discussion), Bayesian Statistics 7, Oxford University Press, 199-213 J. M. Bernardo, M. J. Bayarri, J. Berger, A. P. Dawid, D. Heckerman, A.F.M. Smith, and M. West (Eds.) (2003).
9. T. L. Graves, A framework for expressing and estimating arbitrary statistical models using Markov chain Monte Carlo, Los Alamos National Laboratory Technical Report LA-UR-03-5934 (2003a).
10. T. L. Graves, An introduction to YADAS. yadas.lanl.gov (2003b).
11. D. Spiegelhalter, A. Thomas, and N. Best, WinBUGS Version 1.3 User Manual (2000).
12. M. Hamada, H. F. Martz, C. S. Reese, T. Graves, V. Johnson, and A. G. Wilson, A fully Bayesian approach for combining multilevel failure information in fault tree quantification and optimal follow-on resource allocation, Reliability Engineering and System Safety 86, 297-305 (2004).
13. R. Klamann and A. Koehler, GROMIT: Graphical Modeling Tool for System Statistical Structure, Los Alamos National Laboratory, Los Alamos, NM (2004).