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 prerequisites: STAT 4520 OR STAT 5520 OR MATH 4520 OR MATH 5520. Same as STAT 5430.
instructor(s)
Kleiber, William Paul
Primary Instructor
- Spring 2019 / Fall 2020 / Fall 2021 / Spring 2023 / Spring 2024
