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Journals / Türkiye İstatistik Derneği İstatistik Dergisi / 2026 / Volume: 14 Issue: 1

A Compound Positively Dependent Farlie-Gumbel-Morgenstern Bivariate Copula

Selim Orhun Susam(MUNZUR UNIVERSITY)0000-0001-7896-9055
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Publication Date
2022-07-31
DOI
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AI Summary & Key Takeaways

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

The new copula performs best for the real data having moderate dependence structure.

📌 3 Key Takeaways

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Objective & Hypothesis:In this study, we propose a two parameter Farlie-Gumbel-Morgenstern (FGM) copula that maintains membership in the family in a way while adding the extra dependence parameter to the model by using the compound method.
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Key Findings & Data:Also, we assess the performance of the new compound FGM copula among all the most used two-parameter families of FGM copulas.
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Conclusion & Impact:The new copula performs best for the real data having moderate dependence structure.
🔬Design:Modeling & Simulation
📍Scope:Comprehensive Sample
⚙️Variables:Copula · compound disribution · fgm copula

Abstract

In this study, we propose a two parameter Farlie-Gumbel-Morgenstern (FGM) copula that maintains membership in the family in a way while adding the extra dependence parameter to the model by using the compound method. Also, we assess the performance of the new compound FGM copula among all the most used two-parameter families of FGM copulas. The new copula performs best for the real data having moderate dependence structure.

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Cite This Article

Susam, S. O. (2022). A Compound Positively Dependent Farlie-Gumbel-Morgenstern Bivariate Copula. Türkiye İstatistik Derneği İstatistik Dergisi, Volume: 14 Issue: 1. https://ajindex.com/articles/1562012

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