Bayesian prediction based on type-I censored data from a mixture of Burr type XII distribution and its reciprocal

Autor:	K. E. Ahmad, Z. F. Jaheen, Heba S. Mohammed
Rok vydání:	2012
Předmět:	Statistics and Probability Burr distribution Monte Carlo method Prediction interval Observable Markov chain Monte Carlo Hybrid Monte Carlo symbols.namesake Statistics symbols Applied mathematics Statistics Probability and Uncertainty Reciprocal Monte Carlo molecular modeling Mathematics
Zdroj:	Statistics. 46:787-797
ISSN:	1029-4910 0233-1888
DOI:	10.1080/02331888.2011.555550
Popis:	This paper is concerned with the problem of obtaining Bayesian prediction bounds of future observables from a finite mixture of Burr type XII distribution with its reciprocal based on type-I censored data. We consider the one-sample and two-sample prediction schemes using the Markov chain Monte Carlo algorithm. Numerical examples are given to illustrate the procedures and the accuracy of prediction intervals is investigated via extensive Monte Carlo simulation.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::c75b7af3c10946edb04344a5bc12b2fa https://doi.org/10.1080/02331888.2011.555550 Zobrazit plný text záznamu Plný text ve formátu PDF Plný text ve formátu HTML
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