168 citations · 768 across the 62 of their papers we have counts for
8 papers · 2 filters
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…
Valid model-free spatial prediction
Huiying Mao, Ryan Martin, Brian Reich
Predicting the response at an unobserved location is a fundamental problem in spatial statistics. Given the difficulty in modeling spatial dependence, especially in non-stationary…
Selecting Diverse Models for Scientific Insight
Laura J. Wendelberger, Brian J. Reich, Alyson G. Wilson
Model selection often aims to choose a single model, assuming that the form of the model is correct. However, there may be multiple possible underlying explanatory patterns in a se…
Estimating spatially varying health effects of wildland fire smoke using mobile health data
Lili Wu, Chenyin Gao, Shu Yang +2
Wildland fire smoke exposures are an increasing threat to public health, and thus there is a growing need for studying the effects of protective behaviors on reducing health outcom…