標題: Bayesian inference for Rayleigh distribution under progressive censored sample
作者: Wu, SJ
Chen, DH
Chen, ST
資訊管理與財務金融系 註:原資管所+財金所
Department of Information Management and Finance
關鍵字: highest posterior density interval;predictive density;prediction interval;progressively type II censored sample;reliability function
公開日期: 1-May-2006
摘要: 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 11 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. Copyright (C) 2006 John Wiley & Sons. Ltd.
URI: http://dx.doi.org/10.1002/asmb.615
http://hdl.handle.net/11536/12309
ISSN: 1524-1904
DOI: 10.1002/asmb.615
期刊: APPLIED STOCHASTIC MODELS IN BUSINESS AND INDUSTRY
Volume: 22
Issue: 3
起始頁: 269
結束頁: 279
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