Error bounds for asymptotic approximations of the linear discriminant function when the sample sizes and dimensionality are large
type: Item
instance of: scholarly article
title: Error bounds for asymptotic approximations of the linear discriminant function when the sample sizes and dimensionality are large
zbMATH Open document ID: 0948.62044
author: Yasunori Fujikoshi
published in: Journal of Multivariate Analysis
publication date: 2000-10-03T00:00:00Z
Mathematics Subject Classification ID: 62H30
Mathematics Subject Classification ID: 62E20
zbMATH DE Number: 1471703
zbMATH Keywords: asymptotic approximations
zbMATH Keywords: expected probabilities of misclassification
zbMATH Keywords: linear discriminant function
zbMATH Keywords: error bounds
MaRDI profile type: Publication
full work available at URL: jmva.1999.1862
OpenAlex ID: W2030478261
cites work: Q4251497
cites work: Asymptotic aproximations for EPMC’s of the linear and the quadratic discriminant functions when the sample sizes and the dimension are large
cites work: An Asymptotic Expansion for the Distribution of the Linear Discriminant Function
cites work: Asymptotic expansion of the misclassification probabilities of D- and A- criteria for discrimination from two high dimensional populations using the theory of large dimensional random matrices
cites work: Sharp error bounds for asymptotic expansions of the distribution functions for scale mixtures
DOI: 10.1006/JMVA.1999.1862
description: scientific article; zbMATH DE number 1471703