Research group Mathematical Statistics



Vine Copulas and their Applications

Realistic big data analyses require statistical models accounting for dependence. The class of vine copulas ( has been shown to capture flexibly dependence patterns with tail dependence and asymmetry. Vine copulas significantly extend the Gaussian copula. This two day workshop is devoted to theoretical and methodological advances in vine copula models, including estimation, model selection, simulation, statistical learning, and survival models. Another focus is to showcase...


Prof. Steffen Lauritzen (Humboldt Awardee; University of Copenhagen)

Seminar for Mathematical Statistics: October 17, 2017 at 14:15; Garching, Parkring 11, Room BC1 2.01.10[mehr]

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