A strong large deviation theorem

DOI10.3103/S1066530713020051zbMath1275.60031OpenAlexW2032718975MaRDI QIDQ359869

Cyrille Joutard

Publication date: 23 August 2013

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

Full work available at URL: https://doi.org/10.3103/s1066530713020051

zbMATH Keywords

kernel density estimatorEdgeworth expansionstrong large deviations

Mathematics Subject Classification ID

Nonparametric regression and quantile regression (62G08) Density estimation (62G07) Large deviations (60F10)

Related Items (1)

Asymptotic approximation for the probability density function of an arbitrary sequence of random variables

Cites Work

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• Strong large deviation and local limit theorems
• Multidimensional strong large deviation theorems
• Strong large deviations for arbitrary sequences of random variables
• A Brief Survey of Bandwidth Selection for Density Estimation
• The Probability in the Extreme Tail of a Convolution
• On Deviations of the Sample Mean
• Large deviation properties for empirical quantile-type production functions
• Sharp large deviations in nonparametric estimation
• Large Deviations Limit Theorems for the Kernel Density Estimator
• Sharp large deviations for Gaussian quadratic forms with applications
• Curve Estimates
• Large Deviation Probabilities for Weighted Sums
• The bootstrap and Edgeworth expansion

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