| Course ID: | STAT 8270. 3 hours. |
| Course Title: | Spatial Statistics |
Course
Description: | Models and theories in spatial data, including geostatistics,
lattice data, spatial point patterns, and space-time data. The
course will focus on random field theory, various spatial
regression models, model fitting, inferences and spatial
prediction, with applications to agriculture, environmental
sciences, forestry, and public health. |
| Oasis Title: | SPATIAL STATISTICS |
| Prerequisite: | STAT 4520/6520 and STAT 8260 |
Semester Course
Offered: | Offered spring semester every odd-numbered year. |
| Grading System: | A-F (Traditional) |
|
| Course Objectives: | Students will gain an understanding of the basic theories and
methodologies of spatial statistics, and will learn to analyze
spatial data using standard software. |
| Topical Outline: | Topics to be covered include geostatistics, variograms, spatial
prediction and kriging, lattice data, spatial autoregressive
models, Markov random fields, image analysis, spatial point
patterns, Poisson processes, Cox processes, marked point
processes, space-time modeling. Additional topics may be
presented at the discretion of the instructor. |