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AI Summary & Key Takeaways
AI Insight⚡ TL;DR(Too Long; Didn't Read)
Further, a characterization result of this distribution by using the conditional expectation of generalized order statistics is discussed.
📌 3 Key Takeaways
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Objective & Hypothesis:In this paper some new simple expressions for single and product moments of generalized order statistics from type II exponentiated loglogistic distribution have been obtained.
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Key Findings & Data:The results for order statistics and record values are deduced from the relations derived and some ratio and inverse moments of generalized order statistics are also carried out.
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Conclusion & Impact:Further, a characterization result of this distribution by using the conditional expectation of generalized order statistics is discussed.
🔬Design:Research Article
📍Scope:Comprehensive Sample
⚙️Variables:Exact moments · ratio and inverse moments · generalized order statistics
Abstract
In this paper some new simple expressions for single and product moments of generalized order statistics from type II exponentiated loglogistic distribution have been obtained. The results for order statistics and record values are deduced from the relations derived and some ratio and inverse moments of generalized order statistics are also carried out. Further, a characterization result of this distribution by using the conditional expectation of generalized order statistics is discussed.
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Cite This Article
Kumar, D. (2022). Exact moments of generalized order statistics from type II exponentiated log-logistic distribution. Hacettepe Journal of Mathematics and Statistics, Cilt: 44 - Sayı: 3, 715–733. https://ajindex.com/articles/530298