3 papers
stat.ME2023
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…
stat.ME2023
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…
stat.ME2021
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…