2–3 PM — Cécile Mercadier (Institut Camille Jordan) — [slides]
Hoeffding–Sobol and Möbius decompositions for (tail-)dependence analysisMethods to analyse dependence and tail dependence are well established. Using for instance the copula function or the stable tail dependence function, and their empirical versions, one can construct non parametric statistics, parametric inference, as well as testing or resampling procedures. My talk will reflect upon the use of g sensitivity analysis for extreme value theory and copula modeling. Through my recent publications, I will explain what their links are and the benefit in mixing these domains. Joint work with Christian Genest, Paul Ressel & Olivier Roustant. Refs:
- C. Mercadier, O. Roustant & C. Genest (2022). Linking the Hoeffding–Sobol and Möbius formulas through a decomposition of Kuo, Sloan, Wasilkowski, and Wozniakowski. Statistics & Probability Letters, vol. 185 [hal-03220809],
- C. Mercadier & P. Ressel (2021). Hoeffding–Sobol decomposition of homogeneous co-survival functions: from Choquet representation to extreme value theory application. Dependence Modeling, 9(1):179–198 [hal-03200817],
- C. Mercadier & O. Roustant (2019). The tail dependograph. Extremes, 22:343–372 [hal-01649596].
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