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math.ST2018
On kernel-based estimation of conditional Kendall's tau: finite-distance bounds and asymptotic behavior
Alexis Derumigny, Jean-David Fermanian
We study nonparametric estimators of conditional Kendall's tau, a measure of concordance between two random variables given some covariates. We prove non-asymptotic bounds with exp…
math.ST2018★ 3 cited
About Kendall's regression
Alexis Derumigny, Jean-David Fermanian
Conditional Kendall's tau is a measure of dependence between two random variables, conditionally on some covariates. We assume a regression-type relationship between conditional Ke…