Header

UZH-Logo

Maintenance Infos

Criteria for Evaluating Dimension-Reducing Components for Multivariate Data


Gervini, D; Rousson, V (2004). Criteria for Evaluating Dimension-Reducing Components for Multivariate Data. The American Statistician, 58(1):72-76.

Abstract

Principal components are the benchmark for linear dimension reduction, but they are not always easy to interpret. For this reason, some alternatives have been proposed in recent years. These methods produce components that, unlike principal components, are correlated and/or have nonorthogonal loadings. This article shows that the criteria commonly used to evaluate principal components are not adequate for evaluating such alternatives, and proposes two new criteria that are more suitable for this purpose.

Abstract

Principal components are the benchmark for linear dimension reduction, but they are not always easy to interpret. For this reason, some alternatives have been proposed in recent years. These methods produce components that, unlike principal components, are correlated and/or have nonorthogonal loadings. This article shows that the criteria commonly used to evaluate principal components are not adequate for evaluating such alternatives, and proposes two new criteria that are more suitable for this purpose.

Statistics

Citations

16 citations in Web of Science®
15 citations in Scopus®
Google Scholar™

Altmetrics

Downloads

51 downloads since deposited on 27 Jun 2009
6 downloads since 12 months
Detailed statistics

Additional indexing

Item Type:Journal Article, refereed, original work
Communities & Collections:04 Faculty of Medicine > Epidemiology, Biostatistics and Prevention Institute (EBPI)
Dewey Decimal Classification:610 Medicine & health
Date:2004
Deposited On:27 Jun 2009 11:27
Last Modified:06 Dec 2017 20:04
Publisher:American Statistical Association
ISSN:0003-1305
Publisher DOI:https://doi.org/10.1198/0003130042863

Download

Download PDF  'Criteria for Evaluating Dimension-Reducing Components for Multivariate Data'.
Preview
Filetype: PDF
Size: 1MB
View at publisher