Bayesian inference from type II doubly censored Rayleigh data

Arturo J. Fernández

Statistics & Probability Letters, 2000, vol. 48, issue 4, 393-399

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.

Keywords: Bayesian; estimation; and; prediction; HPD; estimator; and; interval; Type; II; double; censoring; Rayleigh; distribution; Reliability; function; Order; statistics (search for similar items in EconPapers)
Date: 2000
References: View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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