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Journal Articles Journal of Multivariate Analysis Year : 2023

Extreme Partial Least-Squares

Abstract

We propose a new approach, called Extreme-PLS, for dimension reduction in conditional extreme values settings. The objective is to find linear combinations of covariates that best explain the extreme values of the response variable in a non-linear inverse regression model. The asymptotic normality of the Extreme-PLS estimator is established in the single-index framework and 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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Dates and versions

hal-03165399 , version 1 (10-03-2021)
hal-03165399 , version 2 (22-03-2022)
hal-03165399 , version 3 (05-09-2022)

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Cite

Meryem Bousebata, Geoffroy Enjolras, Stéphane Girard. Extreme Partial Least-Squares. Journal of Multivariate Analysis, 2023, 194, pp.105101. ⟨10.1016/j.jmva.2022.105101⟩. ⟨hal-03165399v3⟩
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