DocumentCode :
1084112
Title :
Bayes estimation of the piece-wise exponential distribution
Author :
Gamerman, Dani
Author_Institution :
Inst. de Matematica, Univ. Federal de Rio de Janeiro, Brazil
Volume :
43
Issue :
1
fYear :
1994
fDate :
3/1/1994 12:00:00 AM
Firstpage :
128
Lastpage :
131
Abstract :
A Bayes method to infer an unknown failure time distribution is presented. The method is based on the piecewise exponential distribution and a relationship between values of the failure rate in successive intervals; it provides smooth estimates of the survival and hazard functions of the distribution. This is accomplished in a model-based framework without resorting to smoothing procedures that require ad-hoc specification of parameters that have no bearing on the data. It is a useful procedure whenever the failure rate is anticipated to be reasonably continuous. Incorporating these beliefs into the model allows a more rational solution to the nonparametric estimation problem. The advantages are illustrated using a real data-set where a smooth estimate of the failure rate is obtained. The method can be used with any possibly-censored data-set and is easily implemented on a microcomputer. The Bayes solution is compared with the classical solution for the problem
Keywords :
Bayes methods; estimation theory; failure analysis; nonparametric statistics; probability; reliability theory; Bayes estimation; failure rate; failure time distribution; hazard function; microcomputer; model-based framework; nonparametric estimation problem; piecewise exponential distribution; successive intervals; survival function; Exponential distribution; Failure analysis; Hazards; Maximum likelihood estimation; Microcomputers; Probability; Smoothing methods; Statistical analysis; Statistical distributions; Stochastic processes;
fLanguage :
English
Journal_Title :
Reliability, IEEE Transactions on
Publisher :
ieee
ISSN :
0018-9529
Type :
jour
DOI :
10.1109/24.285126
Filename :
285126
Link To Document :
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