Asymptotics for \(L_ p\)-norms of Fourier series density estimators

DOI10.1007/BF01888271zbMath0706.62042OpenAlexW2039951174MaRDI QIDQ918597

Lajos Horváth

Publication date: 1990

Published in: Constructive Approximation (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/bf01888271

zbMATH Keywords

weight functionasymptotic normalityWiener processkernel estimatorscentral limit theoremsempirical distributionstationary Gaussian processessmooth densityFourier series density estimatorindependent, identically distributed bounded random variables

Mathematics Subject Classification ID

Asymptotic properties of nonparametric inference (62G20) Nonparametric estimation (62G05) Central limit and other weak theorems (60F05) (L^p)-limit theorems (60F25)

Cites Work

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• Measuring the efficiency of trigonometric series estimates of a density
• Central limit theorems for \(L_ p\)-norms of density estimators
• Limit theorems for stochastic measures of the accuracy of density estimators
• On some global measures of the deviations of density function estimates
• The Selection of Terms in an Orthogonal Series Density Estimator
• On the choice of a truncation point in fourier series density estimation
• On a Quadratic Measure of Deviation of the Projection Estimate of a Distribution Density
• The order of the approximation to a Wiener process by its Fourier series
• The Estimation of Probability Densities and Cumulatives by Fourier Series Methods

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