Generalized Bayes Estimation Based on a Joint Type-II Censored Sample from K-Exponential Populations

被引：7

作者：

Abdel-Aty, Yahia ^{[1
,2
]}

Kayid, Mohamed ^{[3
]}

Alomani, Ghadah ^{[4
]}

机构：

[1] Taibah Univ, Coll Sci, Dept Math, Al Madinah Al Munawarah 30002, Saudi Arabia

[2] Al Azhar Univ, Fac Sci, Dept Math, Nasr City 11884, Egypt

[3] King Saud Univ, Coll Sci, Dept Stat & Operat Res, POB 2455, Riyadh 11451, Saudi Arabia

[4] Princess Nourah Bint Abdulrahman Univ, Coll Sci, Dept Math Sci, POB 84428, Riyadh 11671, Saudi Arabia

来源：

MATHEMATICS | 2023年 / 11卷 / 09期

关键词：

generalized bayes; learning rate parameter; exponential distribution; joint type-II censoring; squared-error loss; Linex loss; general entropy loss; EXACT LIKELIHOOD INFERENCE;

D O I：

10.3390/math11092190

中图分类号：

O1 [数学];

学科分类号：

0701 ; 070101 ;

摘要：

Generalized Bayes is a Bayesian study based on a learning rate parameter. This paper considers a generalized Bayes estimation to study the effect of the learning rate parameter on the estimation results based on a joint censored sample of type-II exponential populations. Squared error, Linex, and general entropy loss functions are used in the Bayesian approach. Monte Carlo simulations were performed to assess how well the different approaches perform. The simulation study compares the Bayesian estimators for different values of the learning rate parameter and different losses.

引用

页数：11

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