Bayesian estimation for the reliability function of two parameter exponential distribution under different loss functions

This paper deals with obtaining the best estimator for the reliability function of a two-parameter exponential distribution using the Bayesian estimation method under four different loss functions: squared error loss function, precautionary loss function, and entropy loss function. The exponential d...

Full description

Saved in:
Bibliographic Details
Main Authors: Abd, Maryam N., Rasheed, Huda A.
Format: Conference Proceeding
Language:English
Subjects:
Bayesian analysis
Maximum likelihood estimation
Maximum likelihood estimators
Monte Carlo simulation
Parameters
Probability distribution functions
Reliability
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:This paper deals with obtaining the best estimator for the reliability function of a two-parameter exponential distribution using the Bayesian estimation method under four different loss functions: squared error loss function, precautionary loss function, and entropy loss function. The exponential distribution prior and Gamma distribution have been assumed as the priors for the scale γ and location δ parameters, respectively. In Bayesian estimation, maximum likelihood estimators have been used as the initial estimators for the two unknown parameters, and the Tierney-Kadane approximation has been effectively employed. The estimators were compared using the Monte-Carlo simulation method based on the integral mean squared error (IMSE).
ISSN:0094-243X
1551-7616
DOI:10.1063/5.0203008