*****COURSES ARE SUBJECT TO CHANGE*****
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. Prerequisite(s): course 207. Enrollment restricted to graduate students.
5 Credits
Year | Fall | Winter | Spring | Summer |
2018-19 |
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2016-17 |
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2014-15 |
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2012-13 |
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2010-11 |
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2008-09 |
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2006-07 |
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While the information on this web site is usually the most up to date, in the event of a discrepancy please contact your adviser to confirm which information is correct.