Positive quadrant dependence tests for copulas

DOI10.1002/cjs.10088zbMath1349.62152OpenAlexW2120626287WikidataQ61719259 ScholiaQ61719259MaRDI QIDQ3086514

Dominik Sznajder, Irène Gijbels, Marek Omelka

Publication date: 30 March 2011

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

Full work available at URL: https://doi.org/10.1002/cjs.10088

zbMATH Keywords

weak convergencecopula functionCramér-von Mises testpositive quadrant dependenceKolmogorov-Smirnov distanceAnderson-Darling test statistic

Mathematics Subject Classification ID

Nonparametric hypothesis testing (62G10) Asymptotic properties of nonparametric inference (62G20) Characterization and structure theory for multivariate probability distributions; copulas (62H05)

Related Items (15)

Testing for Positive Quadrant Dependence ⋮ Confidence band for expectation dependence with applications ⋮ Validation of positive expectation dependence ⋮ A Test for Truncation Invariant Dependence ⋮ A new non-parametric test for testing positive quadrant dependence ⋮ When copulas and smoothing met: an interview with Irène Gijbels ⋮ A test when the Fisher information may be infinite, exemplified by a test for marginal independence in extreme value distributions ⋮ Testing tail monotonicity by constrained copula estimation ⋮ Nonparametric tests for tail monotonicity ⋮ Testing for positive expectation dependence ⋮ Validation of positive quadrant dependence ⋮ A new family of copula-based concordance orderings of random pairs: properties and nonparametric tests ⋮ Truncation invariant copulas and a testing procedure ⋮ A Compendium of Copulas ⋮ Positive quadrant dependence testing and constrained copula estimation

Uses Software

• R
• copula
• copula

Cites Work

• Improved kernel estimation of copulas: weak convergence and goodness-of-fit testing
• Detecting positive quadrant dependence and positive function dependence
• Weak convergence and empirical processes. With applications to statistics
• Estimating the density of a copula function
• Competitors of the Kendall-tau test for testing independence against positive quadrant dependence
• Foundations of Modern Probability
• A semiparametric estimation procedure of dependence parameters in multivariate families of distributions
• Nonparametric estimation of copula functions for dependence modelling
• Some Concepts of Dependence
• Understanding Relationships Using Copulas
• A kolmogorov-smirnov type test for positive quadrant dependence
• A Test of Goodness of Fit

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