A Stress-Strength Reliability Model using Exponential-Gamma(3,$\lambda$) Distribution

TL;DR

This paper introduces a new stress-strength reliability model based on the exponential-gamma distribution, deriving estimators, confidence intervals, and validating with simulations and real data.

Contribution

It develops a novel reliability model using exponential-gamma distribution and provides maximum likelihood estimators, asymptotic distributions, and confidence intervals.

Findings

MLE for the model parameters are derived.

Asymptotic distribution and confidence intervals are established.

Numerical simulations and real data analysis validate the model.

Abstract

One of the important problem in reliability analysis is computation of stress-strength reliability. But it is impractical to compute it in certain situations. So the estimation stay as an alternative solution to get an approximate value of the reliability. There are research papers which deals with stress-strength reliability analysis using statistical distributions. In this paper, a stress-strength reliability model for exponential-gamma$(3,\lambda)$ distribution is introduced. The maximum likelihood estimator (MLE) for the model parameters is derived. Asymptotic distribution and confidence interval for the maximum likelihood estimates of stress-strength reliability, $R=P(X>Y)$, are given. The numerical illustration is performed using Monte Carlo simulations. The results are analyzed with real data analysis.