Bayesian Estimation for Poisson-exponential Model under Progressive Type-II Censoring Data with Binomial Removal and Its Application to Ovarian Cancer Data

被引：20
|
作者：
Singh, Sanjay Kumar
Singh, Umesh
Kumar, Manoj
机构：
[1] Banaras Hindu Univ, Dept Stat, Ctr Interdisciplinary Math Sci, Varanasi, Uttar Pradesh, India
[2] Banaras Hindu Univ, Dept Sci & Technol, Ctr Interdisciplinary Math Sci, Varanasi, Uttar Pradesh, India
来源：
COMMUNICATIONS IN STATISTICS-SIMULATION AND COMPUTATION | 2016年 / 45卷 / 09期
关键词：
General entropy loss function; Poisson-exponential distribution; Progressive type-II censored data with Binomial removals; Squared error loss function; 62F10; 62F15; INFERENCE; SAMPLES;
D O I：
10.1080/03610918.2014.948189
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, we propose Maximum likelihood estimators (MLEs) and Bayes estimators of parameters of Poisson-exponential distribution (PED) under General entropy loss function (GELF) and Squared error loss function (SELF) for Progressive type-II censored data with binomial removals (PT-II CBRs). The MLEs and corresponding Bayes estimators are compared in terms of their risks based on simulated samples from PED. The proposed methodology is illustrated on a real dataset of ovarian cancer.
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页码：3457 / 3475
页数：19
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