Introduces the theory of spatial statistics with applications. Topics include basic theory for continuous stochastic processes, spatial prediction and kriging, simulation, geostatistical methods, likelihood and Bayesian approaches, spectral methods and an overview of modern topics such as nonstationary models, hierarchical modeling, multivariate processes, methods for large datasets and connections to splines. Recommended prerequisite: previous coursework equivalent to one of STAT 3400 or STAT 4010 or STAT 5010 and one of STAT 4520 or STAT 5520 or STAT 5530; all with a minimum grade of C-. Same as STAT 4430.
instructor(s)
Kleiber, William Paul
Primary Instructor
- Spring 2019 / Fall 2020 / Fall 2021 / Spring 2023 / Spring 2024
