DocumentCode :
1347907
Title :
Bayes Estimation of Reliability for the Inverse Gaussian Model
Author :
Padgett, W.J.
Author_Institution :
Department of Mathematics and Statistics; University of South Carolina; Columbia, South Carolina 29208 USA.
Issue :
4
fYear :
1981
Firstpage :
384
Lastpage :
385
Abstract :
Estimation of the reliability function is considered for the inverse Gaussian distribution. When the mean lifetime ¿ is known, the Jeffreys vague prior and the natural conjugate prior for ¿ easily yield Bayes estimators of reliability for squared-error loss. If both ¿ and ¿ are unknown, the Bayes solution for reliability in a compact form is extremely difficult. In this case a modified estimator of reliability can be used which is based on the Bayes estimator obtained for ¿ known. The modified estimator is simpler to calculate than the MVUE. Computer simulations indicate that it is more conservative than either the MVUE or the MLE for small mission times, but performs better than the MLE and MVUE for large times.
Keywords :
Bayesian methods; Gaussian distribution; Inverse problems; Life estimation; Life testing; Lifetime estimation; Maximum likelihood estimation; Parameter estimation; Reliability theory; State estimation; Bayesian estimation; Inverse Gaussian distribution; Life testing; Reliability function;
fLanguage :
English
Journal_Title :
Reliability, IEEE Transactions on
Publisher :
ieee
ISSN :
0018-9529
Type :
jour
DOI :
10.1109/TR.1981.5221127
Filename :
5221127
Link To Document :
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