Inference for Lomax Distribution Based on Type-II Progressively Hybrid Censored Data

Abstract

The mixture of Type-I and Type-II censoring schemes, called the hybrid censoring scheme is quite common in life-testing or reliability experiments. In this paper, we investigate the estimation of parameters from two-parameter Lomax distribution based on Type-II progressively hybrid censored samples. Maximum likelihood estimates for the distribution parameters and the reliability indices are obtained. Bayesian estimates of the unknown parameters and the reliability indices are obtained under square error loss function by using the important sample method and the Lindely Bayes approximation algorithm respectively. Different methods have been compared using Monte Carlo simulations.