A New Avenue in Bayesian Modeling using INLA



26-27 May 2022


Faculty of Sciences – University of Lisbon (Faculdade de Ciências da Univesidade de Lisboa),
Campo Grande
1749-016 Lisboa Portugal
T (+351) 217 500 000


Prof. Håvard Rue and Dr. Janet van Niekerk, Elias Krainski, and Denis Rustand
KAUST – King Abdullah University of Science and Technology


The main purpose of this course is to present new recent developments in integrated nested Laplace approximation (INLA) that is a method for approximate Bayesian inference. Although the INLA methodology focuses on models that can be expressed as latent Gaussian Markov random fields (GMRF), this encompasses a large family of models that are used in practice. INLA has been established as an alternative to other methods such as Markov chain Monte Carlo because of its speed and ease of use via the R-INLA package (https://www.r-inla.org/). The lectures would include sections of presentations of the new results and practical sections with coding to illustrate the results for considering some applications.


Day 1 – May 26

09:00–10:30 Lecture 1: The new frontiers in INLA
Coffee break
11:00–12:30 Lecture 2: Some details and illustration

14:00–15:30 Lecture 3: Skewed regression and PC priors
Coffee break
16:00–17:30 Lecture 4: Practical lesson

Day 2 – May 27

09:00–10:30 Lecture 5: Joint survival and longitudinal models
Coffee break
11:00–12:30 Lecture 6 Practical lesson

14:00–15:30 Lecture 7: Spatio-temporal models
Coffee break
16:00–17:30 Lecture 8: Practical lesson

For more information, click here

Referência Projeto: Projecto FCT: UIDB/00006/2020