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

Authors

  • Mohamed A. Sabry Department of Mathematical Statistics, Faculty of Graduate Studies for Statistical Research, Cairo University, Giza, Egypt
  • Ehab M. Almetwally Department of Statistics, Faculty of Business Administration, Delta University of Science and Technology, Dakahlia Governorate, Egypt
  • Hisham M. Almongy Department of Applied Statistics, Faculty of Commerce, Mansoura University, Dakahlia Governorate, Egypt

Keywords:

Maximum likelihood, maximum product spacing, Bayesian estimation, reliability stress-strength

Abstract

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.

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Published

2021-12-30

How to Cite

A. Sabry, M. ., M. Almetwally, E. ., & M. Almongy, H. . (2021). Monte Carlo Simulation of Stress-Strength Model and Reliability Estimation for Extension of the Exponential Distribution. Thailand Statistician, 20(1), 124–143. Retrieved from https://ph02.tci-thaijo.org/index.php/thaistat/article/view/245853

Issue

Vol. 20 No. 1 (2022): January

Section

Articles