Weighted Uniform Consistency of Kernel Density Estimators

Let fndenote a kernel density estimator of a continuous density f in d dimensions, bounded and positive. Let Ψ(t) be a positive continuous function such that $\|\Psi f^{\beta}\|_{\infty}

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Bibliographische Detailangaben
Veröffentlicht in:	The Annals of probability 2004-07, Vol.32 (3), p.2570-2605
Hauptverfasser:	Giné, Evarist, Koltchinskii, Vladimir, Zinn, Joel
Format:	Artikel
Sprache:	eng
Schlagworte:	60F15 62G07 62G20 Consistent estimators Density Density estimation Estimating techniques Estimators Exact sciences and technology General topics Kernel density estimator Logarithms Mathematical analysis Mathematical functions Mathematical models Mathematics Nonparametric inference Perceptron convergence procedure Probability and statistics Probability theory and stochastic processes Random variables rates of convergence Sciences and techniques of general use Statistics Studies Sufficient conditions Uniform laws weak and strong weighted uniform consistency weighted L∞-norm
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Beschreibung
Zusammenfassung:	Let fndenote a kernel density estimator of a continuous density f in d dimensions, bounded and positive. Let Ψ(t) be a positive continuous function such that $\\|\Psi f^{\beta}\\|_{\infty}
ISSN:	0091-1798 2168-894X
DOI:	10.1214/009117904000000063