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1 IRMA - Institut de Recherche Mathématique Avancée

Abstract : The existence of a Dimension Reduction DR subspace is a common assumption in regression analysis when dealing with high-dimensional predictors. The estimation of such a DR subspace has received considerable attention in the past few years, the most popular method being undoubtedly the Sliced Inverse Regression. We propose in this paper a new estimation procedure of the DR subspace by assuming that the joint distribution of the predictor and the response variables is a finite mixture of distributions. The new method is compared through a simulation study to some classical methods.

Keywords : Dimension reduction Maximum likelihood estimates Mixture of distributions Sliced Inverse Regression





Author: Jean-Luc Dortet-Bernadet - Laurent Gardes -

Source: https://hal.archives-ouvertes.fr/



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