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

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.