On the family of multivariate chi-square copulas

DOI10.1016/J.JMVA.2016.07.007zbMath1349.62179OpenAlexW2485813837MaRDI QIDQ321910

Jean-François Quessy, Marie-Hélène Toupin, Louis-Paul Rivest

Publication date: 14 October 2016

Published in: Journal of Multivariate Analysis (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.jmva.2016.07.007

zbMATH Keywords

parameter estimationKendall's tauspatial interpolationSpearman's rhonormal copulaconcordance measures

Mathematics Subject Classification ID

Directional data; spatial statistics (62H11) Characterization and structure theory for multivariate probability distributions; copulas (62H05)

Related Items (8)

The weighted characteristic function of the multivariate PIT: independence and goodness-of-fit tests ⋮ A flexible Clayton-like spatial copula with application to bounded support data ⋮ Testing the symmetry of a dependence structure with a characteristic function ⋮ On non-central squared copulas ⋮ Semi-parametric copula-based models under non-stationarity ⋮ On nonparametric tests of multivariate meta-ellipticity ⋮ Multivariate failure time distributions derived from shared frailty and copulas ⋮ Goodness-of-fit tests for the family of multivariate chi-square copulas

Cites Work

• Computing the nearest correlation matrix--a problem from finance
• An introduction to copulas.
• Extremes of nonexchangeability
• Copula-based geostatistical modeling of continuous and discrete data including covariates
• The Bivariate Normal Copula
• Dependence Modeling with Copulas
• Goodness-of-fit Procedures for Copula Models Based on the Probability Integral Transformation
• A semiparametric estimation procedure of dependence parameters in multivariate families of distributions
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