Estimating scale-invariant directed dependence of bivariate distributions

DOI10.1016/j.csda.2020.107058OpenAlexW3048149558MaRDI QIDQ85343

Wolfgang Trutschnig, Florian Griessenberger, Robert R. Junker, Robert R. Junker, Florian Griessenberger, Wolfgang Trutschnig

Publication date: January 2021

Published in: Computational Statistics & Data Analysis, Computational Statistics and Data Analysis (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.csda.2020.107058

zbMATH Keywords

copulacorrelationasymmetryinvariancedependencedirection

Mathematics Subject Classification ID

Statistics (62-XX)

Related Items (10)

On quantile based co-risk measures and their estimation ⋮ On a multivariate copula-based dependence measure and its estimation ⋮ Maximal asymmetry of bivariate copulas and consequences to measures of dependence ⋮ Measuring association with Wasserstein distances ⋮ Quantifying directed dependence via dimension reduction ⋮ On weak conditional convergence of bivariate Archimedean and extreme value copulas, and consequences to nonparametric estimation ⋮ Measure of asymmetric association for ordinal contingency tables via the bilinear extension copula ⋮ Rearranged dependence measures ⋮ qad ⋮ Total positivity of copulas from a Markov kernel perspective

Uses Software

• R
• copula
• copula
• qad

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Measuring and testing dependence by correlation of distances
• On a strong metric on the space of copulas and its induced dependence measure
• Detecting Novel Associations in Large Data Sets
• Convergence results for patchwork copulas
• On the empirical multilinear copula process for count data
• Large sample behavior of the Bernstein copula estimator
• The empirical beta copula
• An introduction to copulas.
• Extremes of nonexchangeability
• Conditioning-based metrics on the space of multivariate copulas and their interrelation with uniform and levelwise convergence and iterated function systems
• On nonparametric measures of dependence for random variables
• Strong approximation of copulas
• On approximation of copulas
• An empirical study of the maximal and total information coefficients and leading measures of dependence
• Maximum asymmetry of copulas revisited
• Process-driven direction-dependent asymmetry: identification and quantification of directional dependence in spatial fields
• Review on statistical methods for gene network reconstruction using expression data
• Measuring dependence powerfully and equitably
• An informational measure of correlation
• On measures of dependence
• THE BERNSTEIN COPULA AND ITS APPLICATIONS TO MODELING AND APPROXIMATIONS OF MULTIVARIATE DISTRIBUTIONS
• A Copula‐Based Non‐parametric Measure of Regression Dependence

This page was built for publication: Estimating scale-invariant directed dependence of bivariate distributions