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Statistical Inference for Two Weibull Populations Based on Joint Progressive Type-I Censored Scheme
Volume 17, Issue 2 (2019), pp. 349–362
Osama E. Abo-Kasem   Mazen M. Nassar  

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https://doi.org/10.6339/JDS.201904_17(2).0006
Pub. online: 4 August 2022      Type: Research Article      Open accessOpen Access

Published
4 August 2022

Abstract

In this paper, maximum likelihood and Bayesian methods of estimation are used to estimate the unknown parameters of two Weibull populations with the same shape parameter under joint progressive Type-I (JPT-I) censoring scheme. Bayes estimates of the parameters are obtained based on squared error and LINEX loss functions under the assumption of independent gamma priors. We propose to apply Markov Chain Monte Carlo (MCMC) technique to carry out a Bayesian estimation procedure. The approximate confidence intervals and the credible intervals for the unknown parameters are also obtained. Finally, we analyze a one real data set for illustration purpose.

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Keywords
Joint progressive Type-I censored scheme Weibull distribution Maximum likelihood estimation Confidence bounds Bayesian estimation

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