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stat.ME2023
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…
stat.ME2023
A Neural Network-Based Approach to Normality Testing for Dependent Data
Minwoo Kim, Marc G Genton, Raphael Huser +1
There is a wide availability of methods for testing normality under the assumption of independent and identically distributed data. When data are dependent in space and/or time, ho…
stat.ME2021
Modeling spatial tail dependence with Cauchy convolution processes
Pavel Krupskii, Raphaël Huser
We study the class of dependence models for spatial data obtained from Cauchy convolution processes based on different types of kernel functions. We show that the resulting spatial…