Bayesian prediction of the total time on test using doubly censored Rayleigh data

Mohamed Raqab, Mohamed Madi

    Research output: Contribution to journalArticlepeer-review

    56 Citations (Scopus)

    Abstract

    In a Bayesian setting, and on the basis of a doubly censored random sample of failure times drawn from a Rayleigh distribution Fernandez (2000 Statist. Probab. Lett. 48 393-399) considered the problem of predicting an independent future sample from the same distribution. In this article, we extend his work to include the estimation of the predictive distribution of the total time on test up to a certain failure in a future sample, as well as that of the remaining testing time time until all the items in the original sample have failed. Two examples are used to illustrate the prediction procedure.

    Original languageEnglish
    Pages (from-to)781-789
    Number of pages9
    JournalJournal of Statistical Computation and Simulation
    Volume72
    Issue number10
    DOIs
    Publication statusPublished - Oct 1 2002

    Keywords

    • Gibbs sampling
    • Highest posterior density estimate
    • Incomplete gamma function
    • Natural conjugate prior
    • Order statistics
    • Rayleigh distribution

    ASJC Scopus subject areas

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

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