On a new goodness-of-fit process for families of copulas

DOI10.1002/cjs.10006zbMath1170.62039OpenAlexW2109842956MaRDI QIDQ3636242

Jean-François Quessy, Marie-Hélène Toupin, M'hamed Mesfioui

Publication date: 30 June 2009

Published in: Canadian Journal of Statistics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1002/cjs.10006

zbMATH Keywords

empirical processCramér-von Mises statisticgoodness-of-fit testSpearman's rhopseudo-observationSpearman's dependence function

Mathematics Subject Classification ID

Nonparametric hypothesis testing (62G10) Asymptotic distribution theory in statistics (62E20) Asymptotic properties of nonparametric inference (62G20) Hypothesis testing in multivariate analysis (62H15) Bootstrap, jackknife and other resampling methods (62F40)

Related Items (10)

A goodness-of-fit test based on Kendall's process: Durante's bivariate copula models ⋮ Testing for Bivariate Extreme Dependence Using Kendall's Process ⋮ A Goodness-of-fit Test for Copulas ⋮ Dependence measure for length-biased survival data using copulas ⋮ A test when the Fisher information may be infinite, exemplified by a test for marginal independence in extreme value distributions ⋮ Statistical models and methods for dependence in insurance data ⋮ Goodness-of-fit tests for elliptical and independent copulas through projection pursuit ⋮ Weak convergence of empirical and bootstrapped \(C\)-power processes and application to copula goodness-of-fit ⋮ Goodness-of-fit test for specification of semiparametric copula dependence models ⋮ A new family of Archimedean copulas: the truncated-Poisson family of copulas

Cites Work

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• Model Selection and Semiparametric Inference for Bivariate Failure-Time Data
• Tests of serial independence based on Kendall's process
• Symmetry and dependence properties within a semiparametric family of bivariate copulas
• Semiparametric estimation in copula models
• Pseudo-likelihood ratio tests for semiparametric multivariate copula model selection

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