Bayesian inference for exponentiated inverted Weibull distribution in presence of progressive type II censoring

Abstract

The present article gives the point as well as interval estimates for the parameters and lifetime characteristics as reliability and hazard function of the exponentiated inverted Weibull distribution in presence of progressive type II censored data under classical and Bayesian approach. The point estimates under classical paradigm are obtained with the help of maximum likelihood estimation procedure and in case of Bayesian paradigm, gamma prior is used for both unknown parameters under squared error and linex loss function. The Metropolis-Hasting algorithm is applied to generate MCMC samples from posterior density. In case of interval estimation; bootstrap confidence intervals and highest
posterior density intervals for the unknown parameters are computed. The performance of these estimates are studied on the basis of their simulated risks and length of intervals. Additionally, one real dataset is used to illustrate the proposed censoring technique and a simulation study is used to support the given study.