Date(s) - 2022-11-18
14:00 CET - 15:30 CET
Friday, 18 November, 14:00 – 15:30 CEST
This tutorial is an extension to the book seminar on Empirical Bayesian methods, though open to anyone interested. I assume that participants have a basic understanding of Bayesian statistics. The idea is to give you a starting point for implementing Bayesian models in R.
The tutorial comprises
- an introduction to Markov Chain Monte Carlo simulations, which are used for sampling from a posterior distribution
- 1-2 examples how Bayesian models can be implemented and visualized in R using
- time for exercises / coding on your own
To be able to follow, you should
- have a basic understanding of Bayesian statistics
- know what a linear model is
- be familiar with R and the tidyverse
If you want to code along or join the exercises, you should bring your computer and have R/RStudio running.
In person: ATC room B18, Heidelberg
Meeting ID: 979 0831 5718
- Sarah Kaspar, Centre for Statistical Data Analysis, EMBL Heidelberg, Germany.
Booking is not required. You can still book a ticket to get notified in case anything changes. The seats in the seminar room are limited to 9, no limits for joining via Zoom.
Bookings are closed for this event.