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About kernel-based estimation of conditional Kendall's tau: finite-distance bounds and asymptotic behavior. (arXiv:1810.06234v1 [math.ST])
来源于:arXiv
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 explicit constants, that hold with high
probabilities. We provide "direct proofs" of the consistency and the asymptotic
law of conditional Kendall's tau. A simulation study evaluates the numerical
performance of such nonparametric estimators. 查看全文>>
