Project Team Moise

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Application Domains
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Section: New Results

Multivariate risk indicators

Participant : Clémentine Prieur.

In collaboration with Véronique Maume-Deschamps, Elena Di Bernardino (ISFA, Lyon 1) and Peggy Cenac (Université de Bourgogne), we are interested in defining and estimating new multivariate risk indicators. This is a major issue with many applications (environmental, insurance, ...). Two papers were accepted for publication and one other is submitted. The submitted one deals with the estimation of bivariate tails [56] . In [69] we propose to minimize multivariate risk indicators by using a Kiefer-Wolfowitz approach to the mirror stochastic algorithm. In [4] we present an estimation procedure for multivariate risk indicators making use of a plug-in estimation of level sets of bivariate cumulative distribution functions.