284 citations · 806 across the 87 of their papers we have counts for
7 papers · 2 filters
A Generalized Heckman Model With Varying Sample Selection Bias and Dispersion Parameters
Fernando de S. Bastos, Wagner Barreto-Souza, Marc G. Genton
Many proposals have emerged as alternatives to the Heckman selection model, mainly to address the non-robustness of its normal assumption. The 2001 Medical Expenditure Panel Survey…
Are You All Normal? It Depends!
Wanfang Chen, Marc G. Genton
The assumption of normality has underlain much of the development of statistics, including spatial statistics, and many tests have been proposed. In this work, we focus on the mult…
Test and Visualization of Covariance Properties for Multivariate Spatio-Temporal Random Fields
Huang Huang, Ying Sun, Marc G. Genton
The prevalence of multivariate space-time data collected from monitoring networks and satellites, or generated from numerical models, has brought much attention to multivariate spa…
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…
A Pairwise Hotelling Method for Testing High-Dimensional Mean Vectors
Zongliang Hu, Tiejun Tong, Marc G. Genton
For high-dimensional small sample size data, Hotelling's T2 test is not applicable for testing mean vectors due to the singularity problem in the sample covariance matrix. To overc…
Nonparametric Trend Estimation in Functional Time Series with Application to Annual Mortality Rates
Israel Martínez-Hernández, Marc G. Genton
Here, we address the problem of trend estimation for functional time series. Existing contributions either deal with detecting a functional trend or assuming a simple model. They c…
Vector Autoregressive Models with Spatially Structured Coefficients for Time Series on a Spatial Grid
Yuan Yan, Hsin-Cheng Huang, Marc G. Genton
We propose a parsimonious spatiotemporal model for time series data on a spatial grid. Our model is capable of dealing with high-dimensional time series data that may be collected…