• français
    • English
  • English 
    • français
    • English
  • Login
JavaScript is disabled for your browser. Some features of this site may not work without it.
BIRD Home

Browse

This CollectionBy Issue DateAuthorsTitlesSubjectsJournals BIRDResearch centres & CollectionsBy Issue DateAuthorsTitlesSubjectsJournals

My Account

Login

Statistics

View Usage Statistics

A multiple covariance approach to PLS regression with several predictor groups: Structural Equation Exploratory Regression

Thumbnail
Date
2008
Publisher city
Paris
Publisher
Université Paris-Dauphine
Link to item file
http://hal.archives-ouvertes.fr/hal-00239491/en/
Dewey
Probabilités et mathématiques appliquées
Sujet
Linear Regression; Latent Variables; PLS Path Modelling; PLS Regression; Structural Equation Models; SEER
URI
https://basepub.dauphine.fr/handle/123456789/3757
Collections
  • CEREMADE : Publications
Metadata
Show full item record
Author
Bry, Xavier
Verron, Thomas
Cazes, Pierre
Type
Document de travail / Working paper
Item number of pages
34
Abstract (EN)
A variable group Y is assumed to depend upon R thematic variable groups X 1, ..., X R . We assume that components in Y depend linearly upon components in the Xr's. In this work, we propose a multiple covariance criterion which extends that of PLS regression to this multiple predictor groups situation. On this criterion, we build a PLS-type exploratory method - Structural Equation Exploratory Regression (SEER) - that allows to simultaneously perform dimension reduction in groups and investigate the linear model of the components. SEER uses the multidimensional structure of each group. An application example is given.

  • Accueil Bibliothèque
  • Site de l'Université Paris-Dauphine
  • Contact
SCD Paris Dauphine - Place du Maréchal de Lattre de Tassigny 75775 Paris Cedex 16

 Content on this site is licensed under a Creative Commons 2.0 France (CC BY-NC-ND 2.0) license.