Volume 42, Issue 2 (March 2014)

    Bayesian and Non-Bayesian Estimations under Failure-Censored Partially Accelerated Life Tests

    (Received 28 April 2013; accepted 5 September 2013)

    Published Online: 2014

    CODEN: JTEOAD

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    Abstract

    This article considers the Bayesian and non-Bayesian approaches for estimating the Gompertz distribution parameters and the acceleration factor when the data are obtained under the Type II censoring scheme from a step-stress partially accelerated life test. Both the maximum likelihood and Bayesian estimators of the model parameters are derived. The posterior means and posterior variances are derived under the squared error (SE) loss function using Lindley's approximation procedure. The advantage of this proposed procedure is shown. Monte Carlo simulations are performed under different samples sizes and different parameter values for investigating and comparing the proposed methods of estimation. A non-informative prior on the model parameters is used to make the comparison more meaningful.


    Author Information:

    Ismail, Ali A.
    King Saud University, College of Science, Dept. of Statistics and Operations Research, Riyadh,

    Cairo University, Faculty of Economics & Political Science, Dept. of Statistics, Giza,


    Stock #: JTE20130105

    ISSN: 0090-3973

    DOI: 10.1520/JTE20130105

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    Author
    Title Bayesian and Non-Bayesian Estimations under Failure-Censored Partially Accelerated Life Tests
    Symposium , 0000-00-00
    Committee G03