5 citations · 6 across the 4 of their papers we have counts for
Showing 2025Show all
2 papers · 1 filter
stat.ME2025
Gaussian mixture copulas for flexible dependence modelling in the body and tails of joint distributions
Lídia M. André, Jonathan A. Tawn
Fully describing the entire data set is essential in multivariate risk assessment, since moderate levels of one variable can influence another, potentially leading it to be extreme…
stat.ME2025★ 1 cited
Neural Bayes estimation and selection for complex bivariate extremal dependence models
Lídia M. André, Jennifer L. Wadsworth, Raphaël Huser
Likelihood-free approaches are appealing for performing inference on complex dependence models, either because it is not possible to formulate a likelihood function, or its evaluat…