One- and Two-Sample Bayesian Prediction Intervals Based on Type-II Hybrid Censored Data

被引：31

作者：

Balakrishnan, N. ^{[2
]}

Shafay, A. R. ^{[1
]}

机构：

[1] Fayoum Univ, Dept Math, Al Fayyum, Egypt

[2] McMaster Univ, Dept Math & Stat, Hamilton, ON, Canada

来源：

COMMUNICATIONS IN STATISTICS-THEORY AND METHODS | 2012年 / 41卷 / 09期

关键词：

Bayesian prediction; Exponential distribution; Markov Chain Monte Carlo; Order statistics; Pareto distribution; Type-II hybrid censored sample; EXACT LIKELIHOOD INFERENCE; EXPONENTIAL-DISTRIBUTION; WEIBULL DISTRIBUTION; FISHER INFORMATION; SAMPLING PLANS; MODEL; DISTRIBUTIONS; SCHEMES; BOUNDS;

D O I：

10.1080/03610926.2010.543300

中图分类号：

O21 [概率论与数理统计]; C8 [统计学];

学科分类号：

020208 ; 070103 ; 0714 ;

摘要：

In this article, one- and two-sample Bayesian prediction intervals based on Type-II hybrid censored data are derived. For the illustration of the developed results, the Exponential(theta) and Pareto(alpha, beta) distributions are used as examples. One-sample Bayesian predictive survival function can not be obtained in closed form. Gibbs sampling procedure is therefore used to draw Markov Chain Monte Carlo (MCMC) samples, and they are in turn used to compute the approximate predictive survival function, and the corresponding numerical results are presented.

引用

页码：1511 / 1531

页数：21

共 32 条

[11] Exact likelihood inference for the exponential distribution under generalized type-I and type-II hybrid censoring [J].