STAT 458
Spatio-Temporal Data Fall 2018
Division III Quantitative/Formal Reasoning
This is not the current course catalog

Everything happens somewhere and sometime. But the study of data collected over multiple times and locations requires special methods, due to the dependence structure that relates different observations. In this course, we’ll look at exploring, analyzing, and modeling this kind of information–introducing standard methods for purely time-series and purely spatial data, and moving on to methods that incorporate space and time together. Topics will include autocovariance structures, empirical orthogonal functions, and an introduction to Bayesian hierarchical modeling. We’ll use R to apply these techniques to real-world datasets.