Central limit theorems for conditional empirical and conditional \(U\)-processes of stationary mixing sequences

DOI10.3103/S1066530719030013zbMath1425.60024WikidataQ127199132 ScholiaQ127199132MaRDI QIDQ2335548

B. Nemouchi, Salim Bouzebda

Publication date: 14 November 2019

Published in: Mathematical Methods of Statistics (Search for Journal in Brave)

zbMATH Keywords

stationary sequenceVC-classesabsolutely regular sequencesconditional empirical processesuniform central limit theoremsconditional \(U\)-processes

Mathematics Subject Classification ID

Nonparametric regression and quantile regression (62G08) Density estimation (62G07) Gaussian processes (60G15) Central limit and other weak theorems (60F05) Stationary stochastic processes (60G10)

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The k nearest neighbors smoothing of the relative-error regression with functional regressor, Rates of the strong uniform consistency for the kernel-type regression function estimators with general kernels on manifolds, Uniform in bandwidth consistency of conditional \(U\)-statistics adaptive to intrinsic dimension in presence of censored data, On the variable bandwidth kernel estimation of conditional \(U\)-statistics at optimal rates in sup-norm, General tests of conditional independence based on empirical processes indexed by functions, Uniform consistency and uniform in bandwidth consistency for nonparametric regression estimates and conditional U-statistics involving functional data, Renewal type bootstrap for increasing degree \(U\)-process of a Markov chain, Weak-convergence of empirical conditional processes and conditional \(U\)-processes involving functional mixing data, Uniform consistency and uniform in number of neighbors consistency for nonparametric regression estimates and conditional \(U\)-statistics involving functional data

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