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Journals / Hacettepe Journal of Mathematics and Statistics / 2020 / Cilt: 49 - Sayı: 4

Estimation of stress-strength probability in a multicomponent model based on geometric distribution

Milan Jovanović
Bojana Milošević
Marko Obradović
Pages
1515–1532
Publication Date
2022-10-18
DOI
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AI Summary & Key Takeaways

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

Finally, the methods are applied to real data examples from climatology and sport.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:In this paper, the estimation of the stress-strength probability in a multicomponent model, in the case when all components follow the geometric distribution, is studied.
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Key Findings & Data:A simulation study is performed in order to compare the performance of various estimators.
💡
Conclusion & Impact:Finally, the methods are applied to real data examples from climatology and sport.
🔬Design:Modeling & Simulation
📍Scope:Comprehensive Sample
⚙️Variables:Multicomponent stress-strength · reliability · geometric distribution

Abstract

In this paper, the estimation of the stress-strength probability in a multicomponent model, in the case when all components follow the geometric distribution, is studied. This is the first time that multicomponent models with discrete probability distributions are considered. The MLE, UMVUE and Bayes point estimator, as well as asymptotic and bootstrap confidence intervals are presented. A simulation study is performed in order to compare the performance of various estimators. Finally, the methods are applied to real data examples from climatology and sport.

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Cite This Article

Jovanović, M., Milošević, B., Obradović, M. (2022). Estimation of stress-strength probability in a multicomponent model based on geometric distribution. Hacettepe Journal of Mathematics and Statistics, Cilt: 49 - Sayı: 4, 1515–1532. https://ajindex.com/articles/529688

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