Presented by Fogler Library and Wheatland Geospatial Programs, “Hierarchical Modeling and Analysis of Spatial-Temporal Data in R ” will explore recent advancements in hierarchical random effects models using Markov chain Monte Carlo methods with application and examples for statistical ecology. The focus is on linear and generalized linear modeling frameworks that accommodate spatial and temporal associations. Lecture and exercises offer an applied perspective on model specification, identifiability of parameters, and computational considerations for Bayesian inference from posterior distributions.

Registration is required. Further details and required pre-workshop preparation can be found online.

Webconferencing option available on request. Contact Tony Guay at anthony.p.guay@maine.edu with any questions.

If you are a person with a disability and need an accommodation to participate in this program, please call Cindy Paschal, School of Forest Resources, as early as possible at 581-2841 or cpaschal@maine.edu to discuss your needs.