On the convergence of kernel estimators of probability density functions

DOI10.1007/BF02480937zbMath0515.62034OpenAlexW1975221710WikidataQ122753972 ScholiaQ122753972MaRDI QIDQ1052006

Albert E. Rust, Chris P. Tsokos

Publication date: 1981

Published in: Annals of the Institute of Statistical Mathematics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/bf02480937

zbMATH Keywords

algorithmuniform convergencefast Fourier transformempirical characteristic functionsdensity estimatorsrate of almost sure convergenceconvergence of kernel estimatorsfixed-bandwidth estimatorsreproducing-kernel Hilbert spacesvariable-bandwidth estimators

Mathematics Subject Classification ID

Nonparametric estimation (62G05) Probabilistic methods, stochastic differential equations (65C99)

Related Items (2)

Random approximations to some measures of accuracy in nonparametric curve estimation ⋮ A sharper central limit theorem for sums of random elements in hilbert space

Cites Work

• Complete convergence for weighted sums of arrays of random elements
• Mean square error properties of density estimates
• Consistency properties of nearest neighbor density function estimators
• On Convergence in the $L_2$-Norm of Probability Density Estimates
• Variable Kernel Estimates of Multivariate Densities
• A Nonparametric Estimate of a Multivariate Density Function
• On the Best Obtainable Asymptotic Rates of Convergence in Estimation of a Density Function at a Point
• On Estimation of a Probability Density Function and Mode
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