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Journal Articles Journal of Multivariate Analysis Year : 2022

Advanced topics in Sliced Inverse Regression

Abstract

Since its introduction in the early 90's, the Sliced Inverse Regression (SIR) methodology has evolved adapting to increasingly complex data sets in contexts combining linear dimension reduction with non linear regression. The assumption of dependence of the response variable with respect to only a few linear combinations of the covariates makes it appealing for many computational and real data application aspects. This work proposes an overview of the most active research directions in SIR modeling from multivariate regression models to regularization and variable selection.
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Dates and versions

hal-03367798 , version 1 (06-10-2021)

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Stéphane Girard, Hadrien Lorenzo, Jérôme Saracco. Advanced topics in Sliced Inverse Regression. Journal of Multivariate Analysis, 2022, 188, pp.104852. ⟨10.1016/j.jmva.2021.104852⟩. ⟨hal-03367798⟩
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