Analysis Of Type-II Progressively Hybrid Censored Competing Risks Data

被引：0

作者：

Kundu, Debasis ^{[1
]}

Joarder, Avijit ^{[2
]}

机构：

[1] Indian Inst Technol, Dept Math, Statistics, New Delhi 110016, India

[2] Reserve Bank India, Bombay, Maharashtra, India

来源：

JOURNAL OF MODERN APPLIED STATISTICAL METHODS | 2006年 / 5卷 / 01期

关键词：

Competing risk; maximum likelihood estimator; Type-I and Type-II censoring; Fisher information matrix; asymptotic distribution; bayesian inference; exponential distribution; gamma distribution; Type-II progressive censoring scheme;

D O I：

暂无

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：

A Type-II progressively hybrid censoring scheme for competing risks data is introduced, where the experiment terminates at a pre-specified time. The likelihood inference of the unknown parameters is derived under the assumptions that the lifetime distributions of the different causes are independent and exponentially distributed. The maximum likelihood estimators of the unknown parameters are obtained in exact forms. Asymptotic confidence intervals and two bootstrap confidence intervals are also proposed. Bayes estimates and credible intervals of the unknown parameters are obtained under the assumption of gamma priors on the unknown parameters. Different methods have been compared using Monte Carlo simulations. One real data set has been analyzed for illustrative purposes.

引用

页码：152 / 170

页数：19

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