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Information Sciences Letters

Information Sciences Letters

Abstract

This paper discussed inference for two generalized exponential using the joint type-I progressively hybrid censoring (JPHC-I) scheme. It assumed that the lifetime distribution of the items from the two populations follow generalized exponential distribution. Based on the JPHC-I scheme, we first consider the maximum likelihood estimators of the unknown parameters along with thier asymptotic confidence intervals. Next, we provide the Bayesian inferences of the unknown parameters under the assumptions of independent gamma priors on the scale parameters using squared error (SE) and linear-exponential (LINEX) loss functions. Markov Chain Monte Carlo (MCMC) techniques is applied to carry out the Bayesian estimation procedure and in turn calculate the credible intervals. To evaluate the performance of the estimators, numerical example is carried out.

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