Bayesian inference for Rayleigh distribution under progressive censored sample

機構典藏 > College of Business and Management > Graduate Institute & Department of Statistics > Journal Article > Item 987654321/20717

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Title:	Bayesian inference for Rayleigh distribution under progressive censored sample
Authors:	Wu, Shuo-jye;Chen, Dar-hsin;Chen, Shyi-tien
Contributors:	淡江大學統計學系
Keywords:	highest posterior density interval;predictive density;prediction interval;progressively type II censored sample;reliability function
Date:	2006-05-01
Issue Date:	2009-11-30 12:57:35 (UTC+8)
Publisher:	Wiley-Blackwell
Abstract:	It is often the case that some information is available on the parameter of failure time distributions from previous experiments or analyses of failure time data. The Bayesian approach provides the methodology for incorporation of previous information with the current data. In this paper, given a progressively type II censored sample from a Rayleigh distribution, Bayesian estimators and credible intervals are obtained for the parameter and reliability function. We also derive the Bayes predictive estimator and highest posterior density prediction interval for future observations. Two numerical examples are presented for illustration and some simulation study and comparisons are performed.
Relation:	Applied Stochastic Models in Business and Industry 22(3), pp.269-279
DOI:	10.1002/asmb.615
Appears in Collections:	[Graduate Institute & Department of Statistics] Journal Article

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