Admissible kernel estimators of a multivariate density
type: Item
instance of: scholarly article
title: Admissible kernel estimators of a multivariate density
zbMATH Open document ID: 0653.62027
author: Daren B. H. Cline
published in: The Annals of Statistics
publication date: 1988-01-01T00:00:00Z
review text: A kernel density estimator is defined to be admissible if no other kernel estimator has (among all densities and sample sizes) uniformly smaller mean integrated squared error. Admissible kernel density estimators are precisely those using kernels with nonnegative Fourier transforms bounded by 1. Several examples are given.
Mathematics Subject Classification ID: 62G05
Mathematics Subject Classification ID: 62C15
zbMATH DE Number: 4066144
zbMATH Keywords: kernel density estimator
zbMATH Keywords: mean integrated squared error
zbMATH Keywords: nonnegative Fourier transforms
MaRDI profile type: Publication
full work available at URL: https://doi.org/10.1214/aos/1176351046
OpenAlex ID: W1970074788
DOI: 10.1214/AOS/1176351046
description: scientific article; zbMATH DE number 4066144