Reliability analysis of Kumaraswamy distribution under progressive first-failure censoring

Document Type : Original Scientific Paper

Authors

1 Department of Mathematics, Faculty of Sciences, Arak University, Arak 38156-8-8349, Iran

2 Department of Statistics, Patna University, Patna, Bihar, 800005, India

Abstract

In this article‎, ‎we consider the estimation of the parameters and reliability characteristics of Kumaraswamy distribution using progressive first failure censored samples‎. ‎First‎, ‎we derive the maximum likelihood estimates using an expectation-maximization algorithm and compute the observed information of the parameters that can be used for constructing asymptotic confidence intervals‎. ‎We also compute the Bayes estimates of the parameters using Lindley approximation as well as the Metropolis-Hastings algorithm‎. ‎Furthermore‎, ‎we derive the highest posterior density credible intervals‎. ‎Simulation studies are conducted to evaluate the performance of the point and interval estimators‎. ‎Finally‎, ‎two examples of real data sets are provided to illustrate the proposed procedures.

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