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Single-index Extreme-PLS regression

Abstract : The goal of this communication is to propose a new approach, called Single-index Extreme-PLS, for dimension reduction in regression and adapted to distribution tails. The objective is to find a linear combination of predictors that best explain the extreme values of the response variable in a non-linear inverse regression model. The asymptotic normality of the Single-index Extreme-PLS estimator is established under mild assumptions. The performance of the method is assessed on simulated data. A statistical analysis of French farm income data, considering extreme cereal yields, is provided as an illustration.
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Submitted on : Tuesday, June 22, 2021 - 2:06:36 PM
Last modification on : Monday, February 21, 2022 - 8:22:08 AM
Long-term archiving on: : Thursday, September 23, 2021 - 6:40:13 PM


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  • HAL Id : hal-03267334, version 1



Meryem Bousebata, Geoffroy Enjolras, Stéphane Girard. Single-index Extreme-PLS regression. JDS 2021 - 52èmes Journées de Statistique organisées par la Société Française de Statistique (SFdS), Jun 2021, Nice / Virtual, France. pp.1-6. ⟨hal-03267334⟩



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