Bayesian Estimation of the Scale Parameter of the Marshall-Olkin Exponential Distribution under Progressively Type-II Censored Samples

Abstract

Abstract:This paper studies the Bayes estimator, the maximum likelihood estimator and the approximate likelihood estimator of the scale parameter for the Marshall-Olkin exponential distribution under the progressive type-II censored sample. All the estimators, Bayes estimator, maximum likelihood estimator and approximate likelihood estimator are presented and derived in simple forms. It observed that the Bayes estimator and the maximum likelihood estimator can not be solved analytically, hence it is solved numerically. Finally the comparison method is presented in order to compare the performance between these estimators.

Statistical inferences for type-II hybrid censoring data from the alpha power exponential distribution

“…The advantage of this approach is that it allows the complete lifetimes of at least r units to be recorded before the experiment is stopped. Several authors, such as Banerjee and Kundu [ 6 ], Balakrishnan and Shafay [ 7 ], Singh et al [ 8 ], and Salah [ 9 – 11 ], considered statistical inference under T-IIHC. Dey et al [ 12 ] studied the estimation of the generalized inverted exponential distribution under a HCS.…”

On Progressive Type-II Censored Samples from Alpha Power Exponential Distribution

“…(2) If F 1 � F 2 � • • • � F k � 0 and k � s, then no censoring happens (the complete data case). For progressive censoring and its inferences, one can refer to Balakrishnan [5], Balakrishnan et al [6], Salah [7], Salah [8], Salah [9] and Khan et al [10].…”