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Journals / Hacettepe Journal of Mathematics and Statistics / 2026 / Volume: 47 Issue: 1

On estimating a stress-strength type reliability

M. Mahdizadeh
Pages
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Publication Date
2018-02-01
DOI
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AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

The results show that the estimator could be highly effcient in many situations considered.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:This article deals with estimating an extension of the well-known stress-strength reliability in nonparametric setup.
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Key Findings & Data:By means of Monte Carlo simulations, the proposed estimator is compared with its parametric analogs in the case of exponential distribution.
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Conclusion & Impact:The results show that the estimator could be highly effcient in many situations considered.
🔬Design:Research Article
📍Scope:Comprehensive Sample
⚙️Variables:Judgment ranking · $\ell$-out-of-$k$ system · Robustness

Abstract

This article deals with estimating an extension of the well-known stress-strength reliability in nonparametric setup. By means of Monte Carlo simulations, the proposed estimator is compared with its parametric analogs in the case of exponential distribution. The results show that the estimator could be highly effcient in many situations considered.

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Cite This Article

Mahdizadeh, M. (2018). On estimating a stress-strength type reliability. Hacettepe Journal of Mathematics and Statistics, Volume: 47 Issue: 1. https://ajindex.com/articles/1402979

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References (7)

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  6. McIntyre, G.A. A method for unbiased selective sampling using ranked sets. Australian Journal of Agricultural Research 3, 385-390, 1952.
  7. Pakdaman, Z., and Ahmadi, J. Stress-strength reliability for P(Xr:n1 Y ) for exponential populations using order statistics with application in ranked set sampling. Communications in Statistics: Theory and Methods 37, 898-916, 2008.