Sharp large deviations in nonparametric estimation

DOI10.1080/10485250600819233zbMath1104.62056OpenAlexW2170748753MaRDI QIDQ3423584

Cyrille Joutard

Publication date: 14 February 2007

Published in: Journal of Nonparametric Statistics (Search for Journal in Brave)

Full work available at URL: http://crest.science/RePEc/wpstorage/2002-43.pdf

zbMATH Keywords

Nadaraya-Watson estimatorkernel density estimatorlarge deviation principleEdgeworth expansionCramer's conditionkernel regression estimator

Mathematics Subject Classification ID

Nonparametric regression and quantile regression (62G08) Density estimation (62G07) Asymptotic properties of nonparametric inference (62G20) Large deviations (60F10)

Related Items (13)

Moderate deviation principle in nonlinear bifurcating autoregressive models ⋮ A strong large deviation theorem ⋮ Sharp large deviations under Bernstein's condition ⋮ Sharp large deviation results for sums of independent random variables ⋮ Multidimensional strong large deviation results ⋮ Strong large deviations for arbitrary sequences of random variables ⋮ Large and moderate deviation principles for nonparametric recursive kernel distribution estimators defined by stochastic approximation method ⋮ Sharp moderate and large deviations for sample quantiles ⋮ Data-driven wavelet-Fisz methodology for nonparametric function estimation ⋮ Large deviations theorems in nonparametric regression on functional data ⋮ Cramér type moderate deviations for random fields ⋮ Large and moderate deviations principles for kernel estimators of the multivariate regression ⋮ Sharp large deviations for a class of normalized L-statistics and applications

Cites Work

• Moderate deviations and large deviations for kernel density estimators
• Vitesse de convergence de l'approximation de Pareto généralisée de la loi des excès
• On Deviations of the Sample Mean
• Large Deviations Limit Theorems for the Kernel Density Estimator
• Sharp large deviations for Gaussian quadratic forms with applications
• Some Large Deviations Limit Theorems in Conditional Nonparametric Statistics
• The bootstrap and Edgeworth expansion
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