Statistical Modeling of Spatial and Time Series Data

STA 644L

Introduction to Bayesian modeling for data with spatial and/or time dependence. Exploratory analysis of spatial (point referenced and areal) and time series data. Gaussian processes and generalizations. Extending hierarchical Bayesian linear models and generalized linear models. Spatial models: CAR, SAR, kriging and time series models: ARM, ARMA, dynamic linear models. Computational methods for model fitting and diagnostics. Prerequisite: Statistical Science 360 or 601/602L or equivalent. Instructor: Staff

Prerequisites

Prerequisite: Statistical Science 360 or 601 or 602L

Curriculum Codes
  • R
  • QS
Typically Offered
Spring Only