284 citations · 806 across the 87 of their papers we have counts for
11 papers · 1 filter
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…
A Stochastic Generator of Global Monthly Wind Energy with Tukey -and- Autoregressive Processes
Jaehong Jeong, Yuan Yan, Stefano Castruccio +1
Quantifying the uncertainty of wind energy potential from climate models is a very time-consuming task and requires a considerable amount of computational resources. A statistical…
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…
Likelihood Approximation With Hierarchical Matrices For Large Spatial Datasets
Alexander Litvinenko, Ying Sun, Marc G. Genton +1
We use available measurements to estimate the unknown parameters (variance, smoothness parameter, and covariance length) of a covariance function by maximizing the joint Gaussian l…
ExaGeoStat: A High Performance Unified Software for Geostatistics on Manycore Systems
Sameh Abdulah, Hatem Ltaief, Ying Sun +2
We present ExaGeoStat, a high performance framework for geospatial statistics in climate and environment modeling. In contrast to simulation based on partial differential equations…
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…
Multivariate Functional Data Visualization and Outlier Detection
Wenlin Dai, Marc G. Genton
This article proposes a new graphical tool, the magnitude-shape (MS) plot, for visualizing both the magnitude and shape outlyingness of multivariate functional data. The proposed t…
Reducing Storage of Global Wind Ensembles with Stochastic Generators
Jaehong Jeong, Stefano Castruccio, Paola Crippa +1
Wind has the potential to make a significant contribution to future energy resources. Locating the sources of this renewable energy on a global scale is however extremely challengi…