Objective Bayesian analysis of Pareto distribution under progressive Type-II censoring
AbstractIn this paper, objective Bayesian analysis of Pareto distributions under progressive Type-II censoring is considered. Three types of noninformative priors (Jeffreys prior, two reference priors and two general forms of second order probability matching prior) are given. We show that one of the reference priors is also the second order probability matching prior (PMP). However, this reference prior, as well as the Jeffreys prior and PMPs, are related to the censoring scheme of life tests. Thus the other reference prior is preferred, and the proprieties of the posterior are discussed based on it. The simulation shows that the second reference prior leads to the required frequentist property. A real data from Crowley and Hu (1977) is analyzed for the purpose of illustration.
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Bibliographic InfoArticle provided by Elsevier in its journal Statistics & Probability Letters.
Volume (Year): 82 (2012)
Issue (Month): 10 ()
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Web page: http://www.elsevier.com/wps/find/journaldescription.cws_home/622892/description#description
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- N. Balakrishnan, 2007. "Progressive censoring methodology: an appraisal," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer, vol. 16(2), pages 211-259, August.
- Chansoo Kim & Jinhyouk Jung & Younshik Chung, 2011. "Bayesian estimation for the exponentiated Weibull model under Type II progressive censoring," Statistical Papers, Springer, vol. 52(1), pages 53-70, February.
- N. Balakrishnan, 2007. "Rejoinder on: Progressive censoring methodology: an appraisal," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer, vol. 16(2), pages 290-296, August.
- Zeinab Amin, 2008. "Bayesian inference for the Pareto lifetime model under progressive censoring with binomial removals," Journal of Applied Statistics, Taylor & Francis Journals, vol. 35(11), pages 1203-1217.
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