Conditional independence testing via weighted partial copulas
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Publication:2101473
DOI10.1016/J.JMVA.2022.105120OpenAlexW3036315602MaRDI QIDQ2101473
Pascal Bianchi, François Portier, Kevin Elgui
Publication date: 6 December 2022
Published in: Journal of Multivariate Analysis (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1016/j.jmva.2022.105120
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- A consistent characteristic function-based test for conditional independence
- Asymptotics of empirical copula processes under non-restrictive smoothness assumptions
- U-processes: Rates of convergence
- A note on bootstrap approximations for the empirical copula process
- An estimate on the supremum of a nice class of stochastic integrals and U-statistics
- Lectures on the nearest neighbor method
- Partial and average copulas and association measures
- Conditional copulas, association measures and their applications
- Testing for equality between two copulas
- Tests of independence among continuous random vectors based on Cramér-von Mises functionals of the empirical copula process
- Asymptotics for argmin processes: convexity arguments
- Some special Vapnik-Chervonenkis classes
- An asymptotic decomposition for multivariate distribution-free tests of independence
- Asymptotic normality of nonparametric tests for independence
- Asymptotic distributions of multivariate rank order statistics
- Consistent nonparametric regression. Discussion
- Asymptotic normality of multivariate linear rank statistics in the non- i.i.d. case
- Uniform consistency of the kernel conditional Kaplan-Meier estimate
- Nonparametric estimation of pair-copula constructions with the empirical pair-copula
- About tests of the ``simplifying assumption for conditional copulas
- On the weak convergence of the empirical conditional copula under a simplifying assumption
- Weak convergence of empirical copula processes
- Weak convergence and empirical processes. With applications to statistics
- Tests of independence and randomness based on the empirical copula process
- Smooth minimum distance estimation and testing with conditional estimating equations: uniform in bandwidth theory
- Nonparametric tests of independence between random vectors
- Local efficiency of a Cramér\,-\,von Mises test of independence
- Estimation of a Conditional Copula and Association Measures
- Estimation of a Copula when a Covariate Affects only Marginal Distributions
- UNIFORM CONVERGENCE RATES FOR KERNEL ESTIMATION WITH DEPENDENT DATA
- A NONPARAMETRIC HELLINGER METRIC TEST FOR CONDITIONAL INDEPENDENCE
- Regression Quantiles
- Panning for Gold: ‘Model-X’ Knockoffs for High Dimensional Controlled Variable Selection
- Conditional Distance Correlation
- Variable Selection via Additive Conditional Independence
- An empirical process approach to the uniform consistency of kernel-type function estimators
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