The popular workshops series on computational skills and biodiversity informatics from the GGBC is back! We start off with a completely new course taught by Ferran Sayol at the University of Gothenburg. A brief introduction to mixed models using a Bayesian framework. The basic theory behind mixed models practice and hands-on exercises on how to run Bayesian mixed models in R using the MCMCglmm package.
Bayesian generalized mixed models
This course is a brief introduction to mixed models using a Bayesian framework. First, we will see the basic theory behind mixed models and how Bayesian inference can be used to estimate the parameters of our model. Then, we will practice on how to run Bayesian mixed models in R using the MCMCglmm package. In this practical part, we will start from the basics on how to specify the model, run-it and check the output, following with some exercises on how to modify our models to include random effects or change the prior expectations. Finally, we will see how to add special types of random effects, like the effect of phylogenetic relatedness, which is often used in comparative analysis involving several species.
To sign up, send 3 lines of motivation to join the course to Matthias Obst. Sign up deadline 12/3.
2020-03-19 12:00 - 17:00
Botan building, Gothenburg University Last signup date:
12 March 2020
Course teachers: Ferran Sayol and Matthias Obst
Recommended background: Basic knowledge and experience in R.
Course level: PhD level (motivated Master's students welcome)
Fee: No fee
Food: Lunch will be provided for all course participants
Contact: Ferran Sayol (firstname.lastname@example.org) and Matthias Obst (email@example.com)