Estimation and Hypothesis Testing for Exponential Lifetime Models with Double Censoring and Prior Information
نویسنده
چکیده
In this paper, on the basis of a doubly censored sample and in a Bayesian framework, the problem of estimating the mean lifetime, hazard rate, and survival function of the exponential lifetime model is addressed. Bayes estimators under squared-error loss functions are obtained in closed forms. Highest posterior density (HPD) estimators and credible intervals are computed using iterative methods. A Bayesian approach to hypothesis testing is also presented. Optimal answers to hypothesis testing problems are obtained in terms of Bayes factors. Both oneand two-sided tests are considered. Finally, an illustrative numerical example is included. JEL Classification Codes: C120, C130.
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