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Bayesian estimation for generalized exponential distribution based on progressive type-I interval censoring

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Abstract

In this study, we consider the Bayesian estimation of unknown parameters and reliability function of the generalized exponential distribution based on progressive type-I interval censoring. The Bayesian estimates of parameters and reliability function cannot be obtained as explicit forms by applying squared error loss and Linex loss functions, respectively; thus, we present the Lindley’s approximation to discuss these estimations. Then, the Bayesian estimates are compared with the maximum likelihood estimates by using the Monte Carlo simulations.

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Authors and Affiliations

  1. Science College, Inner Mongolia University of Technology, Hohhot, 010051, China

    Xiu-yun Peng & Zai-zai Yan

Authors
  1. Xiu-yun Peng
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  2. Zai-zai Yan
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Corresponding author

Correspondence to Zai-zai Yan.

Additional information

Supported by the National Natural Science Foundation of China (No. 11161031), Natural Science Foundation of Inner Mongolia (2010MS0116) and Higher school science and technology research project of Inner Mongolia (NJ10085).

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Peng, Xy., Yan, Zz. Bayesian estimation for generalized exponential distribution based on progressive type-I interval censoring. Acta Math. Appl. Sin. Engl. Ser. 29, 391–402 (2013). https://doi.org/10.1007/s10255-013-0222-6

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  • DOI: https://doi.org/10.1007/s10255-013-0222-6

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