Weighted least-squares inference for multivariate copulas based on dependence coefficients - Archive ouverte HAL Accéder directement au contenu
Article Dans Une Revue ESAIM: Probability and Statistics Année : 2015

Weighted least-squares inference for multivariate copulas based on dependence coefficients

Résumé

In this paper, we address the issue of estimating the parameters of general multivariate copulas, that is, copulas whose partial derivatives may not exist. To this aim, we consider a weighted least-squares estimator based on dependence coefficients, and establish its consistency and asymptotic normality. The estimator's performance on finite samples is illustrated on simulations and a real dataset.
Fichier principal
Vignette du fichier
paper-revised-5.pdf (408.34 Ko) Télécharger le fichier
Origine : Fichiers produits par l'(les) auteur(s)
Loading...

Dates et versions

hal-00979151 , version 1 (15-04-2014)
hal-00979151 , version 2 (05-05-2014)
hal-00979151 , version 3 (17-08-2014)
hal-00979151 , version 4 (13-11-2014)
hal-00979151 , version 5 (13-11-2014)
hal-00979151 , version 6 (22-10-2015)

Identifiants

Citer

Gildas Mazo, Stéphane Girard, Florence Forbes. Weighted least-squares inference for multivariate copulas based on dependence coefficients. ESAIM: Probability and Statistics, 2015, 19, pp.746 - 765. ⟨10.1051/ps/2015014⟩. ⟨hal-00979151v6⟩
647 Consultations
602 Téléchargements

Altmetric

Partager

Gmail Facebook X LinkedIn More