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Bayesian inference from type II doubly censored Rayleigh data

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  • Fernández, Arturo J.

Abstract

In this paper we present a Bayesian approach to inference in reliability studies based on type II doubly censored data from a Rayleigh distribution. We also consider the problem of predicting an independent future sample from the same distribution in a Bayesian setting. The results can be used to predict the failure-time of a k-out-of-m system. Bayes estimators are obtained in nice closed forms. Highest posterior density (HPD) and maximum likelihood (ML) estimators, and HPD intervals can readily be computed using iterative methods.

Suggested Citation

  • Fernández, Arturo J., 2000. "Bayesian inference from type II doubly censored Rayleigh data," Statistics & Probability Letters, Elsevier, vol. 48(4), pages 393-399, July.
    • Handle: RePEc:eee:stapro:v:48:y:2000:i:4:p:393-399
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    References listed on IDEAS

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    1. Fanhui Kong & Heliang Fei, 1996. "Limit theorems for the maximum likelihood estimate under general multiply Type II censoring," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 48(4), pages 731-755, December.
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    1. Arturo Fernández, 2010. "Bayesian estimation and prediction based on Rayleigh sample quantiles," Quality & Quantity: International Journal of Methodology, Springer, vol. 44(6), pages 1239-1248, October.
    2. Soliman, Ahmed A. & Al-Aboud, Fahad M., 2008. "Bayesian inference using record values from Rayleigh model with application," European Journal of Operational Research, Elsevier, vol. 185(2), pages 659-672, March.

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