Contents
Nonlinear models are central to ecology (e.g. growth, species interactions, thermal responses, SDMs), yet fitting them to data often goes beyond classical GLMMs. Bayesian statistics offers a powerful solution. In this hands-on workshop, we will learn how to use brms to flexibly specify, fit, and interpret nonlinear prediction models with coding effort that barely exceeds lme4, and apply them to real ecological questions.
General knowledge of statistical modeling is needed (ANOVA, linear regression, generalized linear models). Some experience with Bayesian statistics is helpful, but not required.
Lecturer
Dr Benjamin Rosenbaum
Benjamin is a Computational Ecologist with a PhD in Applied Mathematics, based in iDiv’s ‘Theory in Biodiversity group’. Here, his research focuses on statistical methods for species interactions and population dynamics. Through his work as a statistical advisor, he has been involved in many biodiversity-related projects across all iDiv. He also offers statistical consulting for the whole iDiv community.