Generalized Bayes Estimation Based on a Joint Type-II Censored Sample from K-Exponential Populations-Reference-Cited by-同舟云学术

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

Published:2023-05-06 Issue:9 Volume:11 Page:2190
ISSN:2227-7390
Container-title:Mathematics
language:en
Short-container-title:Mathematics

Author:

Abdel-Aty Yahia¹²^ORCID,Kayid Mohamed³^ORCID,Alomani Ghadah⁴^ORCID

Affiliation:

1. Department of Mathematics, College of Science, Taibah University, Al-Madinah Al-Munawarah 30002, Saudi Arabia

2. Department of Mathematics, Faculty of Science, Al-Azhar University, Nasr City 11884, Egypt

3. Department of Statistics and Operations Research, College of Science, King Saud University, P.O. Box 2455, Riyadh 11451, Saudi Arabia

4. Department of Mathematical Sciences, College of Science, Princess Nourah bint Abdulrahman University, P.O. Box 84428, Riyadh 11671, Saudi Arabia

Abstract

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.

Funder

Princess Nourah bint Abdulrahman University, Riyadh, Saudi Arabia

Publisher

MDPI AG

Subject

General Mathematics,Engineering (miscellaneous),Computer Science (miscellaneous)

Link

https://www.mdpi.com/2227-7390/11/9/2190/pdf

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