Estimation of Parameters of Gompertz Distribution Under Progressive Type-II Censoring

Censored Order Statistics

Abstract

In this paper, the problem of estimating unknown parameters of a two
parameter Gompertz distribution is considered based on progressively type-II censored sample. The maximum likelihood (ML) estimators of the parameters are obtained. Bayes estimates are also obtained using different loss functions such as squared error, LINEX and general entropy. The Lindley’s approximation method is used to evaluate these Bayes estimates. Monte Carlo simulation is used for numerical comparison between various estimates developed in this paper.