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Title: Regression type models for extremal dependence Authors:  Linda Mhalla - HEC Montreal (Canada) [presenting]
Miguel de Carvalho - School of Mathematics, University of Edinburgh (Portugal)
Valerie Chavez-Demoulin - University of Lausanne (Switzerland)
Abstract: A vector generalized additive modelling framework is discussed for taking into account the effect of covariates on angular density functions in a multivariate extreme value context. The proposed methods are tailored for settings where the dependence between extreme values may change with time and/or other covariates. We will devise a penalized maximum log-likelihood estimator, discuss details of the estimation procedure, and its consistency and asymptotic normality. The empirical analysis reveals relevant dynamics of the dependence between extreme air temperatures in two alpine resorts during the winter season.