Large and moderate deviations principles for kernel estimators of the multivariate regression

DOI10.3103/S1066530708020051zbMath1282.62141arXivmath/0703341OpenAlexW2010798467MaRDI QIDQ1019536

Mariane Pelletier, Abdelkader Mokkadem, Baba Thiam

Publication date: 2 June 2009

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

Full work available at URL: https://arxiv.org/abs/math/0703341

zbMATH Keywords

Nadaraya-Watson estimatorlarge deviations principlemoderate deviations principlerecursive kernel estimator

Mathematics Subject Classification ID

Nonparametric regression and quantile regression (62G08) Estimation in multivariate analysis (62H12) Large deviations (60F10)

Related Items

Pointwise and uniform moderate deviations for nonparametric regression function estimator on functional data ⋮ Multidimensional strong large deviation results ⋮ Large deviation results for the nonparametric regression function estimator on functional data ⋮ Moderate deviations for some nonparametric estimators with errors in variables ⋮ Nonparametric and semiparametric optimal transformations of markers ⋮ Estimation and Inference Procedures for Semiparametric Distribution Models with Varying Linear‐Index ⋮ Large deviations theorems in nonparametric regression on functional data ⋮ Large and moderate deviation principles for recursive kernel estimators of a regression function for spatial data defined by stochastic approximation method

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