Regression Techniques: Alina Kumukova
From Belle Taylor
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Name: Alina Kumukova
Talk Title: Regression-type analysis for block maxima on block maxima
Abstract: In this talk we introduce a regression-type model for the situation where both the response and covariates are extreme. The proposed approach is designed for the setting where both the response and covariates are themselves block maxima, and thus contrarily to standard regression methods it takes into account the key fact that the limiting distribution of suitably standardized componentwise maxima is an extreme value copula. An important target in the proposed framework is the regression manifold, which consists of a family of regression lines obeying the latter asymptotic result. To learn about the proposed model from data, we employ a Bernstein polynomial prior on the space of angular densities which leads to an induced prior on the space of regression manifolds. Numerical studies suggest a good performance of the proposed methods, and a finance real-data illustration reveals interesting aspects on the comovements of extreme losses between two leading stock markets. This is a joint work with M. de Carvalho and G. dos Reis.
This talk is a contributed talk at EVA 2021.