Open Access
September, 1988 Asymptotic Performance Bounds for the Kernel Estimate
Luc Devroye
Ann. Statist. 16(3): 1162-1179 (September, 1988). DOI: 10.1214/aos/1176350953

Abstract

We consider an arbitrary sequence of kernel density estimates $f_n$ with kernels $K_n$ possibly depending upon $n$. Under a mild restriction on the sequence $K_n$, we obtain inequalities of the type $E\big(\int|f_n - f|\big) \geq (1 + o(1))\Psi(n, f),$ where $f$ is the density being estimated and $\Psi(n, f)$ is a function of $n$ and $f$ only. The function $\psi$ can be considered as an indicator of the difficulty of estimating $f$ with any kernel estimate.

Citation

Download Citation

Luc Devroye. "Asymptotic Performance Bounds for the Kernel Estimate." Ann. Statist. 16 (3) 1162 - 1179, September, 1988. https://doi.org/10.1214/aos/1176350953

Information

Published: September, 1988
First available in Project Euclid: 12 April 2007

zbMATH: 0671.62041
MathSciNet: MR959194
Digital Object Identifier: 10.1214/aos/1176350953

Subjects:
Primary: 60E15
Secondary: 62G05

Keywords: $L_1$ error , Characteristic function , Density estimation , Inequalities‎ , kernel estimate , performance bounds

Rights: Copyright © 1988 Institute of Mathematical Statistics

Vol.16 • No. 3 • September, 1988
Back to Top