Bayesian Estimations under the Weighted LINEX Loss Function Based on Upper Record Values

7Citations
Citations of this article
5Readers
Mendeley users who have this article in their library.

This article is free to access.

Abstract

The essential objective of this research is to develop a linear exponential (LINEX) loss function to estimate the parameters and reliability function of the Weibull distribution (WD) based on upper record values when both shape and scale parameters are unknown. We perform this by merging a weight into LINEX to produce a new loss function called the weighted linear exponential (WLINEX) loss function. Then, we utilized WLINEX to derive the parameters and reliability function of the WD. Next, we compared the performance of the proposed method (WLINEX) in this work with Bayesian estimation using the LINEX loss function, Bayesian estimation using the squared-error (SEL) loss function, and maximum likelihood estimation (MLE). The evaluation depended on the difference between the estimated parameters and the parameters of completed data. The results revealed that the proposed method is the best for estimating parameters and has good performance for estimating reliability.

Cite

CITATION STYLE

APA

Al-Duais, F. S. (2021). Bayesian Estimations under the Weighted LINEX Loss Function Based on Upper Record Values. Complexity, 2021. https://doi.org/10.1155/2021/9982916

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free