Limiting behavior of the perturbed empirical distribution functions evaluated at \(U\)-statistics for strongly mixing sequences of random variables

DOI10.1155/S1048953397000026zbMath0873.62050OpenAlexW2114222490MaRDI QIDQ1357890

Publication date: 27 July 1997

Published in: Journal of Applied Mathematics and Stochastic Analysis (Search for Journal in Brave)

Full work available at URL: https://eudml.org/doc/47718

zbMATH Keywords

law of the iterated logarithm invariance principle \(U\)-statistic almost sure representation perturbed empirical distribution function strongly mixing sequences of random variables

Mathematics Subject Classification ID

Asymptotic distribution theory in statistics (62E20) Asymptotic properties of nonparametric inference (62G20) Order statistics; empirical distribution functions (62G30) Strong limit theorems (60F15) Functional limit theorems; invariance principles (60F17)

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Local polynomial estimation of nonparametric simultaneous equations models ⋮ A weak convergence result for sequential empirical processes under weak dependence ⋮ Testing conditional independence via empirical likelihood ⋮ Specification testing in nonparametric AR‐ARCH models ⋮ TESTING STRUCTURAL CHANGE IN PARTIALLY LINEAR MODELS ⋮ Central limit theorem of the smoothed empirical distribution functions for asymptotically stationary absolutely regular stochastic processes ⋮ Panel nonparametric regression with fixed effects ⋮ Smooth coefficient models with endogenous environmental variables ⋮ Semiparametric estimation of moment condition models with weakly dependent data ⋮ Discontinuities in robust nonparametric regression with α-mixing dependence

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