4 papers · 1 filter
Random forests for binary geospatial data
Arkajyoti Saha, Abhirup Datta
The manuscript develops new method and theory for non-linear regression for binary dependent data using random forests. Existing implementations of random forests for binary data c…
A causal inference framework for spatial confounding
Brian Gilbert, Abhirup Datta, Joan A. Casey +1
Over the past few decades, addressing "spatial confounding" has become a major topic in spatial statistics. However, the literature has provided conflicting definitions, and many p…
Graph-constrained Analysis for Multivariate Functional Data
Debangan Dey, Sudipto Banerjee, Martin Lindquist +1
Functional Gaussian graphical models (GGM) used for analyzing multivariate functional data customarily estimate an unknown graphical model representing the conditional relationship…
Consistency of common spatial estimators under spatial confounding
Brian Gilbert, Elizabeth L. Ogburn, Abhirup Datta
This paper addresses the asymptotic performance of popular spatial regression estimators of the linear effect of an exposure on an outcome under ``spatial confounding" -- the prese…