Geospatial Conditional Random Fields: A Probabilistic Model for Explaining Spatial Tesselations

This paper introduces a probabilistic method for modeling (geo-)spatial tesselations. We propose a new architecture of conditional random fields in two dimensions to estiamte the determinants of spatial groupings.

Scalable Spatio-Temporal Autoregressive Models for Large Non-Gaussian Multivariate Data

Very large spatio-temporal lattice data are becoming increasingly common across a variety of disciplines. However, estimating interdependence across space, time, and outcomes in large lattice data sets remains challenging, as existing approaches are …

Accounting for Immunity in Spatial Processes: The Spatial Susceptibility Model

Political scientists frequently study spatially interdependent processes, such as policy diffusion, democratization, or the spread of violent conflict. Existing studies of such mechanisms typically rely on the spatio-temporal autoregressive (STAR) …


velox is an R package for performing fast extraction and manipulation operations on geospatial raster data.


BoostLines is an R package providing highly scalable geometric line operations for planar networks.

New Spatial Data on Ethnicity: Introducing SIDE

Research on ethnic politics and political violence has benefited substantially from the growing availability of cross-national, geo-coded data on ethnic settlement patterns. However, because existing datasets represent ethnic homelands using …


MapColoring is an R package implementing graph-theoretic optimal contrast coloring of polygon maps.


Convenient access to PRIO GRID raster data from R.