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arXiv · 2608.06214

Optimal Designs in Multicomponent Stress Strength Reliability for the Unit Generalized Rayleigh Distribution

Rajat Das·Yogesh Mani Tripathi·Tanmay Kayal
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Abstract

A unified inferential framework is developed to address the stress-strength reliability of multicomponent systems under progressive Type II censoring. The maximum likelihood estimate of reliability is obtained using an expectation-maximization algorithm, followed by the determination of the corresponding Fisher information matrix and confidence intervals based on the missing-value principle. To facilitate a comparative inferential assessment, maximum product spacing estimates are also developed. By employing both informative and non-informative prior models, a comprehensive analysis is conducted within a Bayesian framework, and suitable summaries are obtained using the Markov chain Monte Carlo algorithm. The performance of all the estimators is analyzed through an extensive simulation study. Finally, a practical application of the proposed methodology is presented using a reliability data set. Furthermore, we determine optimal progressive censoring strategies using three different optimality measures and discuss their usefulness in reliability studies.

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Rajat Das, Yogesh Mani Tripathi, Tanmay Kayal. 2026-08-06. Optimal Designs in Multicomponent Stress Strength Reliability for the Unit Generalized Rayleigh Distribution. https://arxiv.org/abs/2608.06214

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