Bayesian spatial statistics and modeling represent a robust inferential framework where uncertainty in spatial processes is explicitly quantified through probability distributions. This approach ...

The Spatial Scan Statistic is one of the most important methods for detecting and monitoring spatial disease clusters. Usually it is assumed that disease cases follow a Poisson or Binomial ...

Dealing with an autocorrelated response variable is a frequent problem in regression. Using R, it is easy to visualize and analyze this type of data using spatial statistics. We will discuss the meat ...

The rapid advancement of spatial and single-cell omics technologies has revolutionized molecular biosciences by enabling high-resolution profiling of gene ...

COLUMBUS, Ohio - For the first time, researchers have been able to combine different climate models using spatial statistics - to project future seasonal temperature changes in regions across North ...

This course covers specialized methods and models that have been created for performing statistical analysis on spatial data. Students will learn basic statistical concepts and how to apply them to ...