This repository contains the code for the paper Meta-Uncertainty in Bayesian Model Comparison: https://arxiv.org/abs/2210.07278
Note that the R code is structured as a package, thus requiring a local
installation with subsequent loading via
library(MetaUncertaintyPaper)
.
The current paper code uses a highly experimental version of the ggsimplex R package. Install it from GitHub via
devtools::install_github('marvinschmitt/ggsimplex')
The R environment is captured with renv
. Install the renv
package
and load the environment with
renv::restore()
The package requirements of the Python environment (except BayesFlow,
see below) are captured in the requirements.txt
file. Recreate the
environment using
pip install -r requirements.txt
The amortized model comparison network (BayesFlow) in Experiment 3 uses
BayesFlow at commit
c4208418ad19b6648be216cfe013c8f5317a652c
:
https://github.com/stefanradev93/BayesFlow/tree/c4208418ad19b6648be216cfe013c8f5317a652c.
Should you fail to install this BayesFlow version or encounter
unexpected errors, you can load the trained neural networks’ weights
from the folder python/checkpoints_exp3/
and avoid re-training the
network.