Malaysian Journal of Mathematical Sciences, September 2022, Vol. 16, No. 3
Classical and Bayesian Estimation in Exponential Power Distribution under Type-I Progressive Hybrid Censoring with Binomial Removals
Kishan, R. and Sangal, P. K.
Corresponding Email: prabhat.sangal@ignou.ac.in
Received date: 19 July 2020
Accepted date: 4 July 2022
Abstract:
This article deals with the classical and Bayesian estimation in exponential power distribution
based on Type-I progressive hybrid censoring with binomial removals at each stage. Based on
the considered censoring scheme, the maximum likelihood estimates and their coverage probabilities
are computed by the Monte Carlo simulation technique. MCMC technique is used to obtain
the Bayes estimates under the informative priors. The performance of both the approaches
is evaluated in terms of their absolute bias and mean square error (MSE) as well as the width
of the confidence interval. Applicability of the suggested approach is illustrated by analysis of
a real-life dataset.
Keywords: Type-I progressive hybrid censoring; binomial removals; Monte Carlo simulation technique; MCMC technique; coverage probability
Indexing
