Testing for equality between conditional copulas given discretized conditioning events
DOI10.48550/arXiv.2008.09498arXiv2008.09498OpenAlexW4309196677MaRDI QIDQ110517
Jean-David Fermanian, Alexis Derumigny, Aleksey Min, Alexis Derumigny, Jean-David Fermanian, Aleksey Min
Publication date: 21 August 2020
Published in: Canadian Journal of Statistics (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/2008.09498
Nonparametric hypothesis testing (62G10) Asymptotic properties of nonparametric inference (62G20) Measures of association (correlation, canonical correlation, etc.) (62H20) Characterization and structure theory for multivariate probability distributions; copulas (62H05) Statistics (62-XX)
Cites Work
- Testing the simplifying assumption in high-dimensional vine copulas
- A general framework for testing homogeneity hypotheses about copulas
- Statistical testing of covariate effects in conditional copula models
- Time-dependent copulas
- On testing equality of pairwise rank correlations in a multivariate random vector
- Multivariate extensions of Spearman's rho and related statistics
- On the simplified pair-copula construction -- simply useful or too simplistic?
- Multivariate conditional versions of Spearman's rho and related measures of tail dependence
- Testing for equality between two copulas
- Bootstrap methods: another look at the jackknife
- About tests of the ``simplifying assumption for conditional copulas
- A classification point-of-view about conditional Kendall's tau
- Analyzing dependent data with vine copulas. A practical guide with R
- Weak convergence and empirical processes. With applications to statistics
- Score tests for covariate effects in conditional copulas
- On kernel-based estimation of conditional Kendall's tau: finite-distance bounds and asymptotic behavior
- Detecting breaks in the dependence of multivariate extreme-value distributions
- \(K\)-sample problem using strong approximations of empirical copula processes
- On tests for symmetry and radial symmetry of bivariate copulas towards testing for ellipticity
- ESTIMATORS BASED ON KENDALL'S TAU IN MULTIVARIATE COPULA MODELS
- Nonparametric testing for no covariate effects in conditional copulas
- ON THE METHOD OF PAIRED COMPARISONS
- The elements of statistical learning. Data mining, inference, and prediction
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