1 citations · 2 across the 3 of their papers we have counts for
6 papers
A Bayesian approach to identify changepoints in spatio-temporal ordered categorical data: An application to COVID-19 data
Siddharth Rawat, Abe Durrant, Adam Simpson +3
Although there is substantial literature on identifying structural changes for continuous spatio-temporal processes, the same is not true for categorical spatio-temporal data. This…
Re-thinking Spatial Confounding in Spatial Linear Mixed Models
Kori Khan, Candace Berrett
In the last two decades, considerable research has been devoted to a phenomenon known as spatial confounding. Spatial confounding is thought to occur when there is multicollinearit…
A Bayesian change point model for spatio-temporal data
Candace Berrett, Brianne Gurney, David Arthur +2
Urbanization of an area is known to increase the temperature of the surrounding area. This phenomenon -- a so-called urban heat island (UHI) -- occurs at a local level over a perio…
Nonstationary Spatial Prediction of Soil Organic Carbon: Implications for Stock Assessment Decision Making
Mark D. Risser, Catherine A. Calder, Veronica J. Berrocal +1
The Rapid Carbon Assessment (RaCA) project was conducted by the US Department of Agriculture's National Resources Conservation Service between 2010-2012 in order to provide contemp…
Modeling Efficiency of Foreign Aid Allocation in Malawi
Philip A. White, Candace Berrett, E. Shannon Neeley-Tass +1
The Open Aid Malawi initiative has collected an unprecedented database that identifies as much location-specific information as possible for each of over 2500 individual foreign ai…
Bayesian Spatial Binary Classification
Candace Berrett, Catherine A. Calder
In analyses of spatially-referenced data, researchers often have one of two goals: to quantify relationships between a response variable and covariates while accounting for residua…