An Efficient Bayesian Estimation of Ordered Parameters of Two Exponential Distributions

Hideki NAGATSUKA  Toshinari KAMAKURA  Tsunenori ISHIOKA 

Publication
IEICE TRANSACTIONS on Fundamentals of Electronics, Communications and Computer Sciences  Vol.E92-A  No.7  pp.1608-1614
Publication Date: 2009/07/01
Online ISSN: 1745-1337
Print ISSN: 0916-8508
Type of Manuscript: Special Section PAPER (Special Section on Recent Advances in Technologies for Assessing System Reliability)
Category: 
Keyword: 
Bayesian inference,  constrained parameters,  isotonic regression,  maximum likelihood estimation,  Akaike's Bayesian information criterion, 

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Summary: 
The situations where several population parameters need to be estimated simultaneously arise frequently in wide areas of applications, including reliability modeling, survival analysis and biological study. In this paper, we propose Bayesian methods of estimation of the ordered parameters of the two exponential populations, which incorporate the prior information about the simple order restriction, but sometimes breaks the order restriction. A simulation study shows that the proposed estimators are more efficient (in terms of mean square errors) than the isotonic regression of the maximum likelihood estimators with equal weights. An illustrative example is finally presented.