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Multivariate data analysis: The French way

Susan Holmes

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Abstract

This paper presents exploratory techniques for multivariate data, many of them well known to French statisticians and ecologists, but few well understood in North American culture. We present the general framework of duality diagrams which encompasses discriminant analysis, correspondence analysis and principal components, and we show how this framework can be generalized to the regression of graphs on covariates.

Chapter information

Source
Deborah Nolan and Terry Speed, eds., Probability and Statistics: Essays in Honor of David A. Freedman (Beachwood, Ohio, USA: Institute of Mathematical Statistics, 2008), 219-233

Dates
First available in Project Euclid: 7 April 2008

Permanent link to this document
https://projecteuclid.org/euclid.imsc/1207580085

Digital Object Identifier
doi:10.1214/193940307000000455

Mathematical Reviews number (MathSciNet)
MR2459953

Zentralblatt MATH identifier
1166.62310

Subjects
Primary: 62H25: Factor analysis and principal components; correspondence analysis 62H20: Measures of association (correlation, canonical correlation, etc.)

Keywords
bootstrap correspondence analysis duality diagram RV-coefficient STATIS

Rights
Copyright © 2008, Institute of Mathematical Statistics

Citation

Holmes, Susan. Multivariate data analysis: The French way. Probability and Statistics: Essays in Honor of David A. Freedman, 219--233, Institute of Mathematical Statistics, Beachwood, Ohio, USA, 2008. doi:10.1214/193940307000000455. https://projecteuclid.org/euclid.imsc/1207580085


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