Estimation Based on Generalized Order Statistics From a Mixture of Two Rayleigh Distributions

Abstract

This article is concerned with the problem of estimating the parameters, reliability and hazard rate functions of the mixture of two Rayleigh distributions (MT RD) based on generalized order statistics (GOS ). The maximum likelihood and Bayes methods of estimation are used for this purpose. The Markov chain Monte Carlo (MCMC) method is used for obtaining the Bayes estimates under the squared error loss and LINEX loss functions. Our results are specialized to progressive Type-II censored order statistics and upper record values. Comparisons are made between Bayesian and maximum likelihood estimators via a Monte Carlo simulation study.