Statistical Inferences of Type-II Progressively Hybrid Censored Fuzzy Data with Rayleigh Distribution
Abstract
This article presents the procedures for the estimation of the parameter of Rayleigh
distribution based on Type-II progressive hybrid censored fuzzy lifetime data. Classical
as well as the Bayesian procedures for the estimation of unknown model parameters has been developed. The estimators obtained here are Maximum likelihood (ML) estimator, Method of moments (MM) estimator, Computational approach (CA) estimator and Bayes estimator. Highest posterior density (HPD) credible intervals of the unknown parameter are obtained by using Markov Chain Monte Carlo (MCMC) technique. For numerical illustration, a real data set has been considered.
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