https://journalajpas.com/index.php/AJPAS <p style="text-align: justify;"><strong>Asian Journal of Probability and Statistics</strong> <strong>(ISSN: 2582-0230) </strong>aims to publish high-quality papers (<a href="https://journalajpas.com/index.php/AJPAS/general-guideline-for-authors">Click here for Types of paper</a>) in all areas of ‘Probability and Statistics’. By not excluding papers based on novelty, this journal facilitates the research and wishes to publish papers as long as they are technically correct and scientifically motivated. The journal also encourages the submission of useful reports of negative results. This is a quality controlled, OPEN peer-reviewed, open-access INTERNATIONAL journal.</p> Asian Journal of Probability and Statistics en-US Asian Journal of Probability and Statistics 2582-0230 https://journalajpas.com/index.php/AJPAS/article/view/835 <p>The stress-strength reliability measure, defined as R = P(Y &lt; X), is a widely used index in reliability analysis, representing the probability that a system’s strength exceeds the applied stress. This paper investigates the Exponential-Gamma stress-strength model, assuming the stress variable follows an exponential distribution while the strength variable follows a gamma distribution. Analytical expressions for the reliability function are derived and generalized to the case of standby redundant systems. Estimation of reliability is developed using maximum likelihood and uniformly minimum variance unbiased approaches, and both exact and asymptotic confidence intervals are obtained. A detailed Monte Carlo simulation study evaluates the finite-sample properties of the proposed estimators, highlighting the superior small-sample performance of the UMVUE and the asymptotic efficiency of the MLE. The practical usefulness of the model is demonstrated through real data applications, showing that the Exponential-Gamma framework provides an effective and tractable tool for modeling system reliability in applied settings.</p> Joyshree Saharia Jonali Gogoi Copyright (c) 2025 Author(s). The licensee is the journal publisher. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. 2025-12-01 2025-12-01 27 12 1 12 10.9734/ajpas/2025/v27i11835