1 citations · 1 across the 4 of their papers we have counts for
4 papers
Principal component analysis balancing prediction and approximation accuracy for spatial data
Si Cheng, Magali N. Blanco, Timothy V. Larson +3
Dimension reduction is often the first step in statistical modeling or prediction of multivariate spatial data. However, most existing dimension reduction techniques do not account…
Variable importance measure for spatial machine learning models with application to air pollution exposure prediction
Si Cheng, Magali N. Blanco, Lianne Sheppard +2
Exposure assessment is fundamental to air pollution cohort studies. The objective is to predict air pollution exposures for study subjects at locations without data in order to opt…
Inference for Heterogeneous Graphical Models using Doubly High-Dimensional Linear-Mixed Models
Kun Yue, Eardi Lila, Ali Shojaie
Inferring the structure of population-level functional connectivity networks from multi-subject functional magnetic resonance imaging data is essential for understanding the connec…
Doubly regularized generalized linear models for spatial observations with high-dimensional covariates
Arjun Sondhi, Si Cheng, Ali Shojaie
A discrete spatial lattice can be cast as a network structure over which spatially-correlated outcomes are observed. A second network structure may also capture similarities among…