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Bayesian analysis of an exponentiated half-logistic distribution under progressively type-II censoring

  • Kang, Suk Bok (2Department of Statistics, Yeungnam University) ;
  • Seo, Jung In (2Department of Statistics, Yeungnam University) ;
  • Kim, Yongku (Department of Statistics, Kyungpook National University)
  • Received : 2013.06.30
  • Accepted : 2013.08.16
  • Published : 2013.11.30

Abstract

This paper develops maximum likelihood estimators (MLEs) of unknown parameters in an exponentiated half-logistic distribution based on a progressively type-II censored sample. We obtain approximate confidence intervals for the MLEs by using asymptotic variance and covariance matrices. Using importance sampling, we obtain Bayes estimators and corresponding credible intervals with the highest posterior density and Bayes predictive intervals for unknown parameters based on progressively type-II censored data from an exponentiated half logistic distribution. For illustration purposes, we examine the validity of the proposed estimation method by using real and simulated data.

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Cited by

  1. Goodness-of-fit tests for the inverse Weibull or extreme value distribution based on multiply type-II censored samples vol.25, pp.4, 2014, https://doi.org/10.7465/jkdi.2014.25.4.903