Statistical inference of type-I hybrid censored inverse Lomax samples

Abstract

In this article, we adopted the classical and Bayesian approach to develop the problem of estimation and prediction of the inverse Lomax distribution under Type-I hybrid censored scheme. Firstly, we presented maximum likelihood estimators and Bayes estimators of the unknown parameters under consideration of squared error loss equation. In Bayesian approach, we used Markov chain Monte-Carlo method by applied importance sampling technique. Asymptotic confidence intervals and Bayes credible intervals are constructed. The estimators are tested by building sim?ulation study. Secondly, For given Type-I hybrid censoring sample Bayesian prediction of future order statistics are formulated (two-sample case). Finally, the numerical computations are adopted on a real data set for illustrating purpose.