ggc

Julia: the unique solution to an optimisation problem

Parametric divisibility of stochastic losses

A probability distribution is n-divisible if its nth convolution root exists. While modeling the dependence structure between several (re)insurance losses by an additive risk factor model, the infinite divisibility, that is the n-divisibility for all …

Estimation of High-dimensional Thorin measures

Estimation of High-dimensional Thorin measures

Estimation of high dimensional generalized gamma convolutions through random projections

Mesure de Thorin et déconvolution en grandes dimensions

Estimation of High-dimensional Thorin measures

Estimation of high dimensional Gamma convolutions through random projection

Multivariate generalized Gamma convolutions are distributions defined by a convolutional semi-parametric structure. Their flexible dependence structures, the marginal possibilities and their useful convolutional expression make them appealing to the …

(Virtual) Estimation of multivariate generalized gamma convolutions through Laguerre expansions

Estimation of multivariate generalized gamma convolutions through Laguerre expansions

Les convolutions généralisées de loi gamma ont été développées par Thorin dans les années 70 pour résoudre des problèmes d'infinie divisibilité des lois log-normale et Pareto. Bien que le cas univarié fut largement étudié, le cas multivarié et les …