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Bayesian and maximum likelihood estimations of the inverted exponentiated half logistic distribution under progressive Type II censoring
Authors:Kyeongjun Lee
Institution:Department of Statistics, Pusan National University, Busan, Korea
Abstract:In this paper, the estimation of parameters, reliability and hazard functions of a inverted exponentiated half logistic distribution (IEHLD) from progressive Type II censored data has been considered. The Bayes estimates for progressive Type II censored IEHLD under asymmetric and symmetric loss functions such as squared error, general entropy and linex loss function are provided. The Bayes estimates for progressive Type II censored IEHLD parameters, reliability and hazard functions are also obtained under the balanced loss functions. However, the Bayes estimates cannot be obtained explicitly, Lindley approximation method and importance sampling procedure are considered to obtain the Bayes estimates. Furthermore, the asymptotic normality of the maximum likelihood estimates is used to obtain the approximate confidence intervals. The highest posterior density credible intervals of the parameters based on importance sampling procedure are computed. Simulations are performed to see the performance of the proposed estimates. For illustrative purposes, two data sets have been analyzed.
Keywords:Asymptotic normality  balanced loss function  Bayes estimation  inverted exponentiated half logistic distribution  Lindley's approximation  progressive Type II censoring
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