99 citations · 233 across the 15 of their papers we have counts for
8 papers · 1 filter
A Spectral Confounder Adjustment for Spatial Regression with Multiple Exposures and Outcomes
Shih-Ni Prim, Yawen Guan, Shu Yang +4
Characterizing social vulnerability is fundamental to disaster response planning. Numerous vulnerability indicators have been developed, but they are typically not validated for th…
An Improved Doubly Robust Estimator Using Partially Recovered Unmeasured Spatial Confounder
Sayli Pokal, Yawen Guan, Honglang Wang +1
Studies in environmental and epidemiological sciences are often spatially varying and observational in nature with the aim of establishing cause and effect relationships. One of th…
A spectral adjustment for spatial confounding
Yawen Guan, Garritt L. Page, Brian J Reich +2
Adjusting for an unmeasured confounder is generally an intractable problem, but in the spatial setting it may be possible under certain conditions. In this paper, we derive necessa…
Kryging: Geostatistical analysis of large-scale datasets using Krylov subspace methods
Suman Majumder, Yawen Guan, Brian J. Reich +1
Analyzing massive spatial datasets using Gaussian process model poses computational challenges. This is a problem prevailing heavily in applications such as environmental modeling,…
A review of spatial causal inference methods for environmental and epidemiological applications
Brian J Reich, Shu Yang, Yawen Guan +3
The scientific rigor and computational methods of causal inference have had great impacts on many disciplines, but have only recently begun to take hold in spatial applications. Sp…
Fast expectation-maximization algorithms for spatial generalized linear mixed models
Yawen Guan, Murali Haran
Spatial generalized linear mixed models (SGLMMs) are popular and flexible models for non-Gaussian spatial data. They are useful for spatial interpolations as well as for fitting re…
Ice Model Calibration Using Semi-continuous Spatial Data
Won Chang, Bledar A. Konomi, Georgios Karagiannis +2
Rapid changes in Earth's cryosphere caused by human activity can lead to significant environmental impacts. Computer models provide a useful tool for understanding the behavior and…
MIMIX: a Bayesian Mixed-Effects Model for Microbiome Data from Designed Experiments
Neal S. Grantham, Brian J. Reich, Elizabeth T. Borer +1
Recent advances in bioinformatics have made high-throughput microbiome data widely available, and new statistical tools are required to maximize the information gained from these d…