IEICE TRANSACTIONS on Fundamentals
An Efficient Bayesian Estimation of Ordered Parameters of Two Exponential Distributions
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.
- Publication
- IEICE TRANSACTIONS on Fundamentals Vol.E92-A No.7 pp.1608-1614
- Publication Date
- 2009/07/01
- Publicized
- Online ISSN
- 1745-1337
- DOI
- 10.1587/transfun.E92.A.1608
- Type of Manuscript
- Special Section PAPER (Special Section on Recent Advances in Technologies for Assessing System Reliability)
- Category
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Hideki NAGATSUKA, Toshinari KAMAKURA, Tsunenori ISHIOKA, "An Efficient Bayesian Estimation of Ordered Parameters of Two Exponential Distributions" in IEICE TRANSACTIONS on Fundamentals,
vol. E92-A, no. 7, pp. 1608-1614, July 2009, doi: 10.1587/transfun.E92.A.1608.
Abstract: 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.
URL: https://global.ieice.org/en_transactions/fundamentals/10.1587/transfun.E92.A.1608/_p
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@ARTICLE{e92-a_7_1608,
author={Hideki NAGATSUKA, Toshinari KAMAKURA, Tsunenori ISHIOKA, },
journal={IEICE TRANSACTIONS on Fundamentals},
title={An Efficient Bayesian Estimation of Ordered Parameters of Two Exponential Distributions},
year={2009},
volume={E92-A},
number={7},
pages={1608-1614},
abstract={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.},
keywords={},
doi={10.1587/transfun.E92.A.1608},
ISSN={1745-1337},
month={July},}
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TY - JOUR
TI - An Efficient Bayesian Estimation of Ordered Parameters of Two Exponential Distributions
T2 - IEICE TRANSACTIONS on Fundamentals
SP - 1608
EP - 1614
AU - Hideki NAGATSUKA
AU - Toshinari KAMAKURA
AU - Tsunenori ISHIOKA
PY - 2009
DO - 10.1587/transfun.E92.A.1608
JO - IEICE TRANSACTIONS on Fundamentals
SN - 1745-1337
VL - E92-A
IS - 7
JA - IEICE TRANSACTIONS on Fundamentals
Y1 - July 2009
AB - 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.
ER -
English
