The Annals of Statistics

Distribution-Free Pointwise Consistency of Kernel Regression Estimate

Wlodzimierz Greblicki, Adam Krzyzak, and Miroslaw Pawlak

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Abstract

An estimate $\sum^n_{i=1} Y_iK((x - X_i)/h)/\sum^n_{j=1} K((x - X_j)/h)$, calculated from a sequence $(X_1, Y_1), \cdots, (X_n, Y_n)$ of independent pairs of random variables distributed as a pair $(X, Y)$, converges to the regression $E\{Y\mid X = x\}$ as $n$ tends to infinity in probability for almost all $(\mu) x \in R^d$, provided that $E|Y| < \infty, h \rightarrow 0$ and $nh^d \rightarrow \infty$ as $n \rightarrow \infty$. The result is true for all distributions $\mu$ of $X$. If, moreover, $|Y| \leq \gamma < \infty$ and $nh^d/\log n \rightarrow \infty$ as $n \rightarrow \infty$, a complete convergence holds. The class of applicable kernels includes those having unbounded support.

Article information

Source
Ann. Statist. Volume 12, Number 4 (1984), 1570-1575.

Dates
First available in Project Euclid: 12 April 2007

Permanent link to this document
https://projecteuclid.org/euclid.aos/1176346815

Digital Object Identifier
doi:10.1214/aos/1176346815

Mathematical Reviews number (MathSciNet)
MR760711

Zentralblatt MATH identifier
0551.62025

JSTOR
links.jstor.org

Subjects
Primary: 62G05: Estimation

Keywords
Nonlinear regression kernel estimate universal consistency

Citation

Greblicki, Wlodzimierz; Krzyzak, Adam; Pawlak, Miroslaw. Distribution-Free Pointwise Consistency of Kernel Regression Estimate. Ann. Statist. 12 (1984), no. 4, 1570--1575. doi:10.1214/aos/1176346815. https://projecteuclid.org/euclid.aos/1176346815.


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