5 papers
A class of skew-multivariate distributions for spatial data
Pavel Krupskii
This paper introduces a class of copula models for spatial data, based on multivariate Pareto-mixture distributions. We explore the tail properties of these models, demonstrating t…
Parsimonious Factor Models for Asymmetric Dependence in Multivariate Extremes
Pavel Krupskii, Boris Béranger
Modelling multivariate extreme events is essential when extrapolating beyond the range of observed data. Parametric models that are suitable for real-world extremes must be flexibl…
Max-convolution processes with random shape indicator kernels
Pavel Krupskii, Raphaël Huser
In this paper, we introduce a new class of models for spatial data obtained from max-convolution processes based on indicator kernels with random shape. We show that this class of…
On factor copula-based mixed regression models
Pavel Krupskii, Bouchra R Nasri, Bruno N Remillard
In this article, a copula-based method for mixed regression models is proposed, where the conditional distribution of the response variable, given covariates, is modelled by a para…
Conditional Normal Extreme-Value Copulas
Pavel Krupskii, Marc G. Genton
We propose a new class of extreme-value copulas which are extreme-value limits of conditional normal models. Conditional normal models are generalizations of conditional independen…