COUDRET, Raphaël; GIRARD, Stéphane; SARACCO, Jerome

doi:10.1016/j.csda.2014.03.006

Métadonnées

Licence d’utilisation du document

COUDRET, Raphaël
Institut de Mathématiques de Bordeaux [IMB]
Quality control and dynamic reliability [CQFD]
Environnements et Paléoenvironnements OCéaniques [EPOC]

GIRARD, Stéphane
Modelling and Inference of Complex and Structured Stochastic Systems [MISTIS]

SARACCO, Jerome
Institut de Mathématiques de Bordeaux [IMB]
Quality control and dynamic reliability [CQFD]
Ecole Nationale Supérieure de Cognitique [ENSC]

Langue

Article de revue

Ce document a été publié dans

Computational Statistics and Data Analysis. 2014-09, vol. 77, p. 285-299

Elsevier

Résumé en anglais

A semiparametric regression model of a q-dimensional multivariate response y on a p-dimensional covariate x is considered. A new approach is proposed based on sliced inverse regression (SIR) for estimating the effective dimension reduction (EDR) space without requiring a prespecified parametric model. The convergence at rate square root of n of the estimated EDR space is shown. The choice of the dimension of the EDR space is discussed. Moreover, a way to cluster components of y related to the same EDR space is provided. Thus, the proposed multivariate SIR method can be used properly on each cluster instead of blindly applying it on all components of y. The numerical performances of multivariate SIR are illustrated on a simulation study. Applications to a remote sensing dataset and to the Minneapolis elementary schools data are also provided. Although the proposed methodology relies on SIR, it opens the door for new regression approaches with a multivariate response.< Réduire

Mots clés en italien

Semiparametric regression model

Dimension reduction

Sliced inverse regression

Multivariate response

Métadonnées

Partager cette publication !

Licence d’utilisation du document

A new sliced inverse regression method for multivariate response

Langue

Ce document a été publié dans

Résumé en anglais

Mots clés en italien

URI

DOI

Origine

Unités de recherche