Navigation auf uzh.ch
Dozierende | Prof. Dr. Sara Martino, Norwegian University of Science and Technology |
Abschluss | Confirmation of participation |
Zielpublikum |
Novice and advanced R users from all professional groups. |
Kosten |
Persons without current employment can register for the UZH/ETH fee upon request. |
Kurssprache | English |
Beschreibung |
This 2-day course with practical sessions aims to give an introduction to the R packages INLA and inlabru, which provide a simple way to perform Bayesian inference for latent Gaussian models (LGMs). LGMs are among the most commonly used classes of models in statistical applications and include generalized linear models, generalized additive models, smoothing spline models, linear state space models, log-Gaussian Cox processes and more. For this class of models INLA provides a fast and reliable inference that is also easy to implement in practice thanks to the R-INLA library. We will also introduce the inlabru library. This allowes to extend the GAM-like model class to more general nonlinear predictor expressions. Both libraries use the "formula'' framework of R to specify a wide variety of models in a familiar and streamlined way which only requires small changes in the code to add or remove random effects, temporal effects, spatial effects and so on. Topics of the course include:
Examples will be presented from the fields of biostatistics, spatial statistics, ecology etc. For all Zurich R Courses participants should bring their own laptops to the course and will be informed by email in advance which packages they need to install. |
Daten | March 17-18 2022 |