Inference On Gompertz Distribution Based On Upper k Record Values

Inference based on upper k records

Abstract

In this paper, we consider the inference based on upper k -record values for a two parameter Gompertz distribution. The maximum likelihood estimators of the parameters are obtained. The Bayes estimates of the parameters are also developed by using Markov chain Monte Carlo method under symmetric and asymmetric loss functions. The problem of predicting the future record values based on past record values is also considered. Finally, a simulation study is performed to find the performance of different estimators developed in this paper.