Statistics

STAT 226 Spatial Statistics

Introduction to the analysis of spatial data: theory of correlation structures and variograms; kriging and Gaussian processes; Markov random fields; fitting models to data; computational techniques; frequentist and Bayesian approaches. (Formerly AMS 245.)

Requirements

Prerequisite(s): STAT 207. Enrollment is restricted to graduate students.

Credits

5

Quarter offered

Winter

Instructor

Herbert Lee, Bruno Sanso