High-probability one-sided confidence intervals in reliability models

Nuclear Science and Engineering

Volumn 126, Issue 2, 1997, Pages 158-167

  Castillo, Enrique ^a   Solares, Cristina ^a   Gómez, Patricia ^a  

^a UNIVERSITY OF CANTABRIA   (Spain)

Author keywords

[No Author keywords available]

Indexed keywords

EID: 0001374617     PISSN: 00295639     EISSN: None     Source Type: Journal    
DOI: 10.13182/NSE97-A24469     Document Type: Article

References (22)

1. S. AHMED, D. R. METCALF, and J. W. PEGRAM, "Uncertainty Propagation in Probabilistic Risk Assessment: A Comparative Study," Trans. Am. Nucl. Soc., 38, 483 (1981).
2. D. C. COX and P. BAYBUTT, "Methods for Uncertainty Analysis: A Comparative Study," Risk Anal., 1, 251 (1981).
3. P. S. JACKSON, R. W. HOCKENBURY, and M. L. YEATER, "Uncertainty Analysis of System Reliability and Availability Assessment," Nucl. Eng. Des., 68, 5 (1981).
4. J. GALAMBOS, The Asymptotic Theory of Extreme Order Statistics, Robert E. Krieger Publishing Company, Malabar, Florida (1987).
5. E. CASTILLO, Extreme Value Theory in Engineering, Academic Press, New York (1988).
6. I. WEISSMAN, "Estimation of Parameters and Large Quantiles Based on the k Largest Observations," J. Am. Stat. Assoc., 73, 812 (1978).
7. J. PICKANDS III, "Statistical Inference Using Extreme Order Statistics," Ann. Stat., 75, 119 (1975).
8. J. PEARL, "Evidential Reasoning Using Stochastic Simulation of Causal Models," Artif. Intelligence, 32, 245 (1987).
9. R. D. SHACHTER and M. A. PEOT, "Simulation Approaches to General Probabilistic Inference on Belief Networks," Uncertainty in Artificial Intelligence, Vol. 5, L. N. KANAL, M. HENRION, R. D. SHACHTER, and J. F. LEMMER, Eds., North Holland, Amsterdam (1990).
10. R. FUNG and K. C. CHANG, "Weighing and Integrating Evidence for Stochastic Simulation in Bayesian Networks," Uncertainty in Artificial Intelligence, Vol. 5, L. N. KANAL, M. HENRION, R. D. SHACHTER, and J. F. LEMMER, Eds., North Holland, Amsterdam (1990).
11. R. M. CHAVEZ and G. F. COOPER, "A Randomized Approximation Algorithm for Probabilistic Inference on Bayesian Belief Networks," Networks, 20, 661 (1990).
12. R. M. CHAVEZ and G. F. COOPER, "An Empirical Evaluation of a Randomized Algorithm for Probabilistic Inference," Uncertainty in Artificial Intelligence, Vol. 2, J. LEMMER, L. N. KANAL, and T. S. LEVITT, Eds., North Holland, Amsterdam (1990).
13. R. BOUCKAERT, "Properties of Bayesian Belief Networks Learning Algorithms," Proc. 10th Conf. Uncertainty in Artificial Intelligence, Seattle, Washington, 1994, p. 102, Morgan Kaufmann Publishers.
14. R. BOUCKAERT, E. CASTILLO, and J. M. GUTIÉRREZ, "A Modified Simulation Scheme for Inference in Bayesian Networks," Int. J. Approximate Reasoning (1995).
15. E. CASTILLO, J. M. GUTIÉRREZ, and A. S. HADI, Expert Systems and Probabilistic Network Models, Springer Verlag, New York (1996).
16. B. STAPLE and F. E. HASKIN, "Analysis of Extreme Top Event Frequency Percentiles Based on Fast Probability Integration," Proc. PSAM-II, San Diego, California, 1994, p. 4619.
17. F. E. HASKIN, B. D. STAPLE, and C. DING, "Efficient Uncertainty Analyses Using Fast Probability Integration," Nucl. Eng. Des., 166, 225 (1996).
18. H. F. MARTZ, R. J. BECKMAN, K. CAMPBELL, D. E. WHITEMAN, and J. M. BOOKER, "A Comparison of Methods for Uncertainty Analysis of Nuclear Power Plant Safety System Fault Tree Models," NUREG/CR-3263, LA-9729-MS, NRC FIN No. A7725, Los Alamos National Laboratory (1983).
19. K. N. FLEMING, A. MOSLEH, and K. DEREMER, "A Systematic Procedure for the Incorporation of Common Cause Events into Risk and Reliability Models," Nucl. Eng. Des., 93, 245 (1986).
20. A. W. MARSHALL and I. OLKIN, "A Multivariate Exponential Distribution," J. Am. Stat. Assoc., 62, 30 (1967).
21. R. L. IMAN and S. C. HORA, "A Robust Measure of Uncertainty Importance for Use in Fault Tree System Analysis," Risk Anal., 10, 3, 401.
22. F. E. HASKIN, M. HUANG, M. K. SASSER, and D. W. STACK, "Mean Importance Measures for Groups of Events in Fault Trees," Nucl. Technol., 106, 155 (1994).