Statistical inference for dependence competing risks model under middle censoring

被引：0

作者：

WANG Yan ^{[1
,2
]}

SHI Yimin ^{[1
]}

WU Min ^{[3
]}

机构：

[1] Department of Applied Mathematics, Northwestern Polytechnical University

[2] School of Economics & Management, Shanghai Maritime University

[3] School of Science, Xi'an Polytechnic University

来源：

Journal of Systems Engineering and Electronics | 2019年 / 30卷 / 01期

基金：

中国国家自然科学基金;

关键词：

middle censoring; dependent competing risks model; Marshall-Olkin bivariate Weibull(MOBW) distribution; acceptance-rejection sampling;

D O I：

暂无

中图分类号：

O212.1 [一般数理统计];

学科分类号：

020208 ; 070103 ; 0714 ;

摘要：

Middle censoring is an important censoring scheme,in which the actual failure data of an observation becomes unobservable if it falls into a random interval. This paper considers the statistical analysis of the dependent competing risks model by using the Marshall-Olkin bivariate Weibull(MOBW) distribution.The maximum likelihood estimations(MLEs), midpoint approximation(MPA) estimations and approximate confidence intervals(ACIs) of the unknown parameters are obtained. In addition, the Bayes approach is also considered based on the Gamma-Dirichlet prior of the scale parameters, with the given shape parameter.The acceptance-rejection sampling method is used to obtain the Bayes estimations and construct credible intervals(CIs). Finally,two numerical examples are used to show the performance of the proposed methods.

引用

页码：209 / 222

页数：14

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