Bayesian inference for the generalized exponential distribution

Mohamed Z. Raqab, Mohamed T. Madi

    Research output: Contribution to journalArticlepeer-review

    57 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 languageEnglish
    Pages (from-to)841-852
    Number of pages12
    JournalJournal of Statistical Computation and Simulation
    Volume75
    Issue number10
    DOIs
    Publication statusPublished - 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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