A central theme in geography is the study of spatial and temporal variations of the phenomena which make up natural and human-dominated environments. This course delves into statistical methods for analyzing phenomena that are correlated in space and/or time. Practical applications of theoretical concepts will be explored through the use of R, a statistical computing software. Topics include the characterization of temporal processes; basic time series models (AR, MA, ARMA, ARIMA); characterization of spatial processes; geostatistics (Kriging and conditional simulation); spatial point processes; visualization of spatiotemporal data; spatiotemporal covariance functions; and spatiotemporal Kriging. At the end of the course, the students will have a firm grounding in the theory of spatiotemporal statistics and understand how to apply these methods to answer questions of geographic interest. Prerequisite: GEOG 2700.
A central theme in geography is the study of spatial and temporal variations of the phenomena which make up natural and human-dominated environments. This course delves into statistical methods for analyzing phenomena that are correlated in space and/or time. Practical applications of theoretical concepts will be explored through the use of R, a statistical computing software. Topics include the characterization of temporal processes; basic time series models (AR, MA, ARMA, ARIMA); characterization of spatial processes; geostatistics (Kriging and conditional simulation); spatial point processes; visualization of spatiotemporal data; spatiotemporal covariance functions; and spatiotemporal Kriging. At the end of the course, the students will have a firm grounding in the theory of spatiotemporal statistics and understand how to apply these methods to answer questions of geographic interest. Prerequisite: GEOG 2700.
