STAT226: 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.)

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

5 credits

Year	Fall	Winter	Spring	Summer
2022-23		Section 01 Bruno Sansó (bsanso)

Comments

Formerly AMS 0245

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