Spatial Statistics

In this course students will be introduced to statistical methodology for data that are collected over space. Following a brief introduction to Bayesian inference and probabilistic programming languages (Stan, NIMBLE, and JAGS), we will investigate how spatial dependence challenges classical modeling assumptions. We will learn about spatial correlation and covariance functions, Poisson point processes, methods for areal data, and methods for geostatistical data including Gaussian process regression and ordinary Kriging. Students will also develop skills in visualizing and summarizing spatially correlated data structures, learn to fit spatial models in R, and develop the theory of spatial statistics. (STAT 0310, STAT 0311 concurrently).