Bayesian inference for the generalized exponential distribution

Mohamed Z. Raqab; Mohamed T. Madi

doi:10.1080/00949650412331299166

Bayesian inference for the generalized exponential distribution

Mohamed Z. Raqab, Mohamed T. Madi

Research output: Contribution to journal › Article › peer-review

64 Citations (Scopus)

Abstract

The two-parameter generalized exponential (GE) distribution was introduced by Gupta and Kundu [Gupta, R.D. and Kundu, D., 1999, Generalized exponential distribution. Australian and New Zealand Journal of Statistics, 41(2), 173-188.]. It was observed that the GE can be used in situations where a skewed distribution for a nonnegative random variable is needed. In this article, the Bayesian estimation and prediction for the GE distribution, using informative priors, have been considered. Importance sampling is used to estimate the parameters, as well as the reliability function, and the Gibbs and Metropolis samplers data sets are used to predict the behavior of further observations from the distribution. Two data sets are used to illustrate the Bayesian procedure.

Original language	English
Pages (from-to)	841-852
Number of pages	12
Journal	Journal of Statistical Computation and Simulation
Volume	75
Issue number	10
DOIs	https://doi.org/10.1080/00949650412331299166
Publication status	Published - Oct 1 2005

Keywords

Bayesian estimation
Bayesian prediction
Generalized exponential distribution
Gibbs and Metropolis sampling
Importance sampling
Life testing

ASJC Scopus subject areas

Statistics and Probability
Modelling and Simulation
Statistics, Probability and Uncertainty
Applied Mathematics

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10.1080/00949650412331299166

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Bayesian inference for the generalized exponential distribution

Abstract

Keywords

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