E-Bayesian estimation and its E-posterior risk of the exponential distribution parameter based on complete and type I censored samples
Ming Han
Communications in Statistics - Theory and Methods, 2020, vol. 49, issue 8, 1858-1872
Abstract:
This article studies E-Bayesian estimation and its E-posterior risk, for failure rate derived from exponential distribution, in the case of the two hyper parameters. In order to measure the estimated risk, the definition of E-posterior risk (expected posterior risk) is proposed based on the definition of E-Bayesian estimation. Moreover, under the different prior distributions of hyper parameters, the formulas of E-Bayesian estimation and formulas of E-posterior risk are given respectively, these estimations are derived based on a conjugate prior distribution for the unknown parameter under the squared error loss function. Monte Carlo simulations are performed to compare the performances of the proposed methods of estimation and a real data set have been analyzed for illustrative purposes, results are compared on the basis of E-posterior risk.
Date: 2020
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Persistent link: https://EconPapers.repec.org/RePEc:taf:lstaxx:v:49:y:2020:i:8:p:1858-1872
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DOI: 10.1080/03610926.2019.1565837
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