Objective Bayesian analysis of JM model in software reliability

被引：6
|
作者：
Lian, Yongqiang [1 ]
Tang, Yincai [1 ]
Wang, Yijun [1 ]
机构：
[1] East China Normal Univ, Sch Stat, Shanghai 200241, Peoples R China
来源：
COMPUTATIONAL STATISTICS & DATA ANALYSIS | 2017年 / 109卷
基金：
中国国家自然科学基金;
关键词：
Software reliability; Objective Bayesian analysis; Jeffreys prior; Reference prior; Probability matching prior; Gibbs sampling; ERROR-DETECTION; GROWTH;
D O I：
10.1016/j.csda.2016.12.006
中图分类号：
TP39 [计算机的应用];
学科分类号：
081203 ; 0835 ;
摘要：
Jelinski Moranda (JM) model is frequently used in software reliability. The objective Bayesian inference was proposed to estimate the parameters of JM model. Jeffreys prior and reference priors have been derived. Besides, the properties of corresponding posteriors were deduced and some modifications were made which made the posterior distributions proper. Then Gibbs sampling was utilized to obtain the Bayesian estimators, credible intervals and coverage probabilities of the parameters. Comparisons in the efficiency of the maximum likelihood estimators and Bayesian estimators under different priors for various sample sizes have been done by simulations and a real data set was analyzed for illustrative purpose. (C) 2016 Elsevier B.V. All rights reserved.
引用
收藏
页码：199 / 214
页数：16
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