E-Bayesian inference for xgamma distribution under progressive type II censoring with binomial removals and their applications

被引:2
|
作者
Pathak, Anurag [1 ]
Kumar, Manoj [1 ,5 ]
Singh, Sanjay Kumar [2 ]
Singh, Umesh [2 ]
Tiwari, Manoj Kumar [3 ,4 ]
Kumar, Sandeep [1 ]
机构
[1] Cent Univ Haryana, Dept Stat, Mahendergarh, India
[2] Banaras Hindu Univ, Dept Stat, Varanasi, India
[3] Sultan Qaboos Univ, Dept Stat, Muscat 123, Oman
[4] Punjab Univ, Dept Stat, Chandigarh, India
[5] Cent Univ Haryana, Dept Stat, Mahendergarh 123031, India
来源
INTERNATIONAL JOURNAL OF MODELLING AND SIMULATION | 2024年 / 44卷 / 03期
关键词
xgamma; PT II CBRs; MLE; bootstrap; E-Bayes inference;
D O I
10.1080/02286203.2022.2161744
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
In this article, we propose E-Bayes estimators of the parameter of xgamma distribution under squared error loss function, general entropy loss function, and linear exponential loss function for progressive type II censored data with binomial removals. The proposed estimators, maximum likelihood estimator, and corresponding Bayes estimators are compared in terms of their risks based on simulated samples from xgamma distribution. The proposed methodology is illustrated on two real data sets of bile duct cancer data and the endurance of deep-groove ball bearings data.
引用
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页码:136 / 155
页数:20
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