Tutorial: Bayesian simulation in R

When

Friday, 18 November, 14:00 – 15:30 CEST

Content

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 rstanarm
• time for exercises / coding on your own

Prerequisites

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.

Location

In person: ATC room B18, Heidelberg

Zoom:

Meeting ID: 979 0831 5718

Passcode: 748208

Organizer

• Sarah Kaspar, Centre for Statistical Data Analysis, EMBL Heidelberg, Germany.

Note

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