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Simulation techniques of Archimedean Copula Estimators: Parametric and Semi-Parametric Approaches
Author(s) -
Nesrine Idiou,
Fatah Benatia
Publication year - 2021
Publication title -
european journal of mathematics and statistics
Language(s) - English
Resource type - Journals
ISSN - 2736-5484
DOI - 10.24018/ejmath.2021.2.3.48
Subject(s) - copula (linguistics) , estimator , parametric statistics , parametric model , computer science , econometrics , mathematics , context (archaeology) , algorithm , statistics , paleontology , biology
In this paper, we look at two different approaches methodologies for copula estimation. The first is based on a parametric approach using MLE and IFM methods, while the second is entirely based on Kendall's tau and spearman's rho in a semi-parametric context, where the margins are estimated non-parametrically. Interestingly, based on R software simulation techniques, the contribution of their algorithms, approach, and illustration was our main focus for this paper. As an application, a class of Archimedean copulas was notably chosen. This particular class of copulas was also presented for censored data to show the estimator's performance even better.

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