Thank you for your registration to the Bayesian statistics workshop.
We start at 10 AM each morning and finish roughly at 17:45 PM.
Location: Akadeemia tee 3, rooms SOC-413 (Oct 2, 3, 17) and SOC-418 (Oct 16). The rooms should be easy to find.
Bring your laptop. We will use RStudio Cloud for the hands-on sessions, so there is no need to install any software beforehand. However, as RStudio Cloud runs in your browser it can sometimes be slow. So, if you wish, you can download R (https://www.r-project.org/), RStudio (https://www.rstudio.com/products/rstudio/download/), and Stan (https://mc-stan.org/users/interfaces/rstan) into your laptop. But if you have any problems with installations, then don’t worry – you can use RStudio Cloud.
Coffee breaks and lunches will be provided.
Don’t forget to bring your digital COVID certificate or a recent negative test.
If you are not friends with git, whole repo (all materials included) can be downloaded as a zip file using "Download ZIP" button under green "Code" button.
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Newer materials on Bayesian modeling by Ülo are available in this repo in docs folder Bayes_eng.pdf (in English) and Bayes_est.pdf (in Estonian). Rest of pdfs in the docs folder are Ülo slides.
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Older materials (last updated Oct-2019) of Bayesian data analysis are available here as an ebook (in Estonian).
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Scripts (and data) is stored in scripts and data folder, respectively. Rmd files in scripts folder need to have paths wrapped into
herefunction for these paths to work.
Taavis course materials were developed using rocker/verse:4.1.0 Docker image, followed by installation of following CRAN and non-cran libraries -- tidyverse, lubridate, here, brms, bayesplot, tidybayes, modelr, rstan, rethinking, loo, rstanarm, mice, naniar, qgcomp.
If you want to give a try to this setup, first you need to get and install Docker.
Pull rocker/verse image
docker pull rocker/verse:4.1.0Start local RStudio server and log in with user "rstudio" and password "yourpassword" (for pw, choose what ever you want)
docker run -e PASSWORD=yourpassword --rm -p 8787:8787 -v /path/to/your/R/projects/folder:/home/rstudio rocker/verse:4.1.0Then required additional R libraries can be installed using regular install.packages() command.