Selection of suitable prior for the Bayesian mixture of a class of lifetime distributions under type-I censored datasets

Syed Mohsin Ali Kazmi, Muhammad Aslam, Sajid Ali and Nasir Abbas

Journal of Applied Statistics, 2013, vol. 40, issue 8, 1639-1658

Abstract: This paper explores the study on mixture of a class of probability density functions under type-I censoring scheme. In this paper, we mold a heterogeneous population by means of a two-component mixture of the class of probability density functions. The parameters of the class of mixture density functions are estimated and compared using the Bayes estimates under the squared-error and precautionary loss functions. A censored mixture dataset is simulated by probabilistic mixing for the computational purpose considering particular case of the Maxwell distribution. Closed-form expressions for the Bayes estimators along with their posterior risks are derived for censored as well as complete samples. Some stimulating comparisons and properties of the estimates are presented here. A factual dataset has also been for illustration.

Date: 2013
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Citations: View citations in EconPapers (2)

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DOI: 10.1080/02664763.2013.789831

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