10 citations · 15 across the 9 of their papers we have counts for
6 papers · 1 filter
Which Parameterization of the Matérn Covariance Function?
Kesen Wang, Sameh Abdulah, Ying Sun +1
The Matérn family of covariance functions is currently the most popularly used model in spatial statistics, geostatistics, and machine learning to specify the correlation between t…
A semi-parametric estimation method for quantile coherence with an application to bivariate financial time series clustering
Cristian F. Jiménez-Varón, Ying Sun, Ta-Hsin Li
In multivariate time series analysis, spectral coherence measures the linear dependency between two time series at different frequencies. However, real data applications often exhi…
Forecasting high-dimensional functional time series: Application to sub-national age-specific mortality
Cristian F. Jiménez-Varón, Ying Sun, Han Lin Shang
We study the modeling and forecasting of high-dimensional functional time series (HDFTS), which can be cross-sectionally correlated and temporally dependent. We introduce a decompo…
Modeling and Predicting Spatio-temporal Dynamics of PM Concentrations Through Time-evolving Covariance Models
Ghulam A. Qadir, Ying Sun
Fine particulate matter (PM) has become a great concern worldwide due to its adverse health effects. PM concentrations typically exhibit complex spatio-temporal var…
Estimation of Spatial Deformation for Nonstationary Processes via Variogram Alignment
Ghulam A. Qadir, Ying Sun, Sebastian Kurtek
In modeling spatial processes, a second-order stationarity assumption is often made. However, for spatial data observed on a vast domain, the covariance function often varies over…
Semiparametric Estimation of Cross-covariance Functions for Multivariate Random Fields
Ghulam A. Qadir, Ying Sun
The prevalence of spatially referenced multivariate data has impelled researchers to develop a procedure for the joint modeling of multiple spatial processes. This ordinarily invol…