The asymptotic distributions of kernel estimators of the mode

44Citations
Citations of this article
5Readers
Mendeley users who have this article in their library.

This article is free to access.

Abstract

In a decreasing sequence of intervals centered on the true mode the normalized kernel estimate of the density converges weakly to a nonstationary Gaussian random process. The expected value of this process is a parabola through the origin. The covariance function of this process depends on the smoothness of the kernel. When the kernel is mean-square differentiable the location of the maximum of this process has a normal distribution. When the kernel is discontinuous the location of the maximum has a distribution related to a solution of the heat equation. © 1982 Springer-Verlag.

References Powered by Scopus

Estimation of the mode

156Citations
N/AReaders
Get full text

Cited by Powered by Scopus

Limit distribution theory for maximum likelihood estimation of a log-concave density

74Citations
N/AReaders
Get full text

Asymptotic normality of a nonparametric estimator of the conditional mode function for functional data

49Citations
N/AReaders
Get full text

Change point estimation by local linear smoothing

39Citations
N/AReaders
Get full text

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Cite

CITATION STYLE

APA

Eddy, W. F. (1982). The asymptotic distributions of kernel estimators of the mode. Zeitschrift Für Wahrscheinlichkeitstheorie Und Verwandte Gebiete, 59(3), 279–290. https://doi.org/10.1007/BF00532221

Readers' Seniority

Tooltip

Professor / Associate Prof. 2

67%

PhD / Post grad / Masters / Doc 1

33%

Readers' Discipline

Tooltip

Mathematics 1

100%

Save time finding and organizing research with Mendeley

Sign up for free