4 papers
Robust Spatial Confounding Adjustment via Basis Voting
Anik Burman, Elizabeth L. Ogburn, Abhirup Datta
Estimating effects of spatially structured exposures is complicated by unmeasured spatial confounders, which undermine identifiability in spatial linear regression models unless st…
Unified calibration and spatial mapping of fine particulate matter data from multiple low-cost air pollution sensor networks in Baltimore, Maryland
Claire Heffernan, Kirsten Koehler, Drew R. Gentner +2
Low-cost air pollution sensor networks are increasingly being deployed globally, supplementing sparse regulatory monitoring with localized air quality data. In some areas, like Bal…
Commentary on Guyll et al. (2023): Misuse of Statistical Method Results in Highly Biased Interpretation of Forensic Evidence
Michael Rosenblum, Elizabeth T. Chin, Elizabeth L. Ogburn +6
Since the National Academy of Sciences released their report outlining paths for improving reliability, standards, and policies in the forensic sciences NAS (2009), there has been…
Visibility graph-based covariance functions for scalable spatial analysis in non-convex domains
Brian Gilbert, Abhirup Datta
We present a new method for constructing valid covariance functions of Gaussian processes for spatial analysis in irregular, non-convex domains such as bodies of water. Standard co…