Monte Carlo Simulation of Stress-Strength Model and Reliability Estimation for Extension of the Exponential Distribution

被引：0
|
作者：
Sabry, Mohamed A. [1 ]
Almetwally, Ehab M. [1 ,2 ]
Almongy, Hisham M. [3 ]
机构：
[1] Cairo Univ, Fac Grad Studies Stat Res, Dept Math Stat, Giza, Egypt
[2] Delta Univ Sci & Technol, Fac Business Adm, Dept Stat, Dakahlia Governorate, Egypt
[3] Mansoura Univ, Fac Commerce, Dept Appl Stat, Dakahlia Governorate, Egypt
来源：
THAILAND STATISTICIAN | 2022年 / 20卷 / 01期
关键词：
Maximum likelihood; maximum product spacing; Bayesian estimation; reliability stress-strength; PARAMETERS;
D O I：
暂无
中图分类号：
O21 [概率论与数理统计]; C8 [统计学];
学科分类号：
020208 ; 070103 ; 0714 ;
摘要：
In this paper, parameter estimation and reliability estimation for the extension of the exponential distribution are discussed. Point estimations of the stress-strength model deliberated. The maximum likelihood, maximum product spacing and Bayesian estimation are obtained. The results of Bayesian estimation are computed under the squared error loss (SEL) based on Markov chain Monte Carlo (MCMC). Monte Carlo simulation introduced to explicate and comparison the precision of the obtained estimators. An empirical study by using real data sets were conducted to support the theoretical aspect.
引用
收藏
页码：124 / 143
页数：20
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