By Haakon Christopher Bakka (NTNU in Norway)
The INLAcourse starts with a general overview of the possibilities in INLA, for applied research and for model development. We will proceed to examples of generalised linear models with several random effects. We discuss the cool ideas making INLA fast; why most likelihoods are near-gaussian in the posterior, how to represent random effects with sparse matrices, and more. The last part of the course is looking at spatial random effects and how they fit into the INLA framework; using the brilliant SPDE approach. Inference in INLA is so fast that we run the examples live in class!
Haakon Bakka is a PhD student in spatial statistics at NTNU in Norway, where his main supervisor is Håvard Rue. His research is on fast spatial inference using R-INLA, where the spatial structure is designed to be consistent with scientific understanding of the underlying process. His applications are focused on species distribution modeling, especially on habitats and abundance of aquatic animals. He has given INLA/SPDE courses in Pamplona (Spain), Zurich (Switzerland), Valencia (Spain), Reykjavik (Iceland) and Moncton (Canada).
For more info contact: Prof. Haavard Rue: email: Haavard.firstname.lastname@example.org
Date: From Monday 20 Feb - Thursday 23 Feb, and from Sunday 26 Feb - Wednesday 1 March 2017
Time: 04:00 PM - 05:30 PM
Location: Building 1, level 4 room 4102