Statistical modelling and inference for covariate-dependent extremal dependence

Diplôme Thèse Statistical modelling and inference for covariate-dependent extremal dependence eng 2018-06-28 author Mhalla Linda 827708 director Ronchetti Elvezio 0000-0003-2231-4556 22756 director Chavez-Demoulin Valérie 10.13097/archive-ouverte/unige:106918 urn:nbn:ch:unige-1069182 GSEM 57 In this thesis, we develop new models for covariate-varying tail dependence structures and propose novel techniques for fitting these models to both block maxima and threshold exceedances data, under the assumptions of asymptotic dependence and asymptotic independence. Our proposals for the flexible incorporation of covariate influence rely on the (vector) generalized additive modelling infrastructure, and are established in a parametric setting and a non-parametric setting where we develop projection techniques enabling the reduction of the problem of characterizing joint tail dependences to the modelling of univariate random variables. Inference is performed by penalized maximum likelihood estimation combined, when applicable, with censored likelihood techniques. The performance of the resulting estimators is assessed either through simulation studies or based on asymptotic distributions. The developed methodologies are illustrated on environmental datasets where dependence between large events is linked to a set of covariates describing time as well as characteristics of the measurement sites. Angular density Asymptotic dependence Asymptotic independence Covariate-adjustment Extreme value theory Generalized additive models Max-stable random vectors Multivariate extreme values Penalized log-likelihood Threshold exceedances Vector generalized additive models Dewey 330/650 9 Faculté d'économie et de management S false 60913a5f-086f-4deb-abc8-d72d8d05e21f Thesis Public Thesis_manuscript.pdf 16681289 application/pdf openAccess Faculté d'économie et de management

Title	Published in	Access level	OA Policy	Year	Views	Downloads

Statistical modelling and inference for covariate-dependent extremal dependence				2018	735	322

Archive ouverte UNIGE

Mhalla, Linda