20 citations · 49 across the 43 of their papers we have counts for
7 papers · 2 filters
A Multi-Resolution Spatial Model for Large Datasets Based on the Skew-t Distribution
Felipe Tagle, Stefano Castruccio, Marc G. Genton
Large, non-Gaussian spatial datasets pose a considerable modeling challenge as the dependence structure implied by the model needs to be captured at different scales, while retaini…
Non-Gaussian Autoregressive Processes with Tukey g-and-h Transformations
Yuan Yan, Marc Genton
When performing a time series analysis of continuous data, for example from climate or environmental problems, the assumption that the process is Gaussian is often violated. Theref…
Diagonal Likelihood Ratio Test for Equality of Mean Vectors in High-Dimensional Data
Zongliang Hu, Tiejun Tong, Marc G. Genton
We propose a likelihood ratio test framework for testing normal mean vectors in high-dimensional data under two common scenarios: the one-sample test and the two-sample test with e…
Bayesian model averaging over tree-based dependence structures for multivariate extremes
Sabrina Vettori, Raphaël Huser, Johan Segers +1
Describing the complex dependence structure of extreme phenomena is particularly challenging. To tackle this issue we develop a novel statistical algorithm that describes extremal…
An Outlyingness Matrix for Multivariate Functional Data Classification
Wenlin Dai, Marc G. Genton
The classification of multivariate functional data is an important task in scientific research. Unlike point-wise data, functional data are usually classified by their shapes rathe…
Full likelihood inference for max-stable data
Raphaël Huser, Clément Dombry, Mathieu Ribatet +1
We show how to perform full likelihood inference for max-stable multivariate distributions or processes based on a stochastic Expectation-Maximisation algorithm, which combines sta…