The hBayesDM (hierarchical Bayesian modeling of Decision-Making tasks) is a user-friendly R package that offers hierarchical Bayesian analysis of various computational models on an array of decision-making tasks. The hBayesDM package uses Stan for Bayesian inference.
(For Windows users) First download and install Rtools from this link: http://cran.r-project.org/bin/windows/Rtools/. For detailed instructions, please go to this link: https://github.com/stan-dev/rstan/wiki/Installing-RStan-on-Windows.
You need to install the hBayesDM from CRAN. The GitHub version precompiles all Stan models, which makes it faster to start MCMC sampling. But it may cause some memory allocation issues on a Windows machine.
(For Mac/Linux users) If you are a Mac user, make sure Xcode is installed. We strongly recommend users install this GitHub version. The GitHub version in the master repository is identical to the CRAN version, except that all models are precompiled in the GitHub version, which saves time for compiling Stan models.
You can install the latest version from github with:
# install 'devtools' if required
if (!require(devtools)) install.packages("devtools")
devtools::install_github("CCS-Lab/hBayesDM")
Please go to hBayesDM Tutorial for more information about the package.
If you encounter a problem or a bug, please use our mailing list: https://groups.google.com/forum/#!forum/hbayesdm-users, or you can directly create an issue on GitHub.
If you used hBayesDM or some of its codes for your research, please cite this paper:
Ahn, W.-Y., Haines, N., & Zhang, L. (2017). Revealing neuro-computational mechanisms of reinforcement learning and decision-making with the hBayesDM package. Computational Psychiatry, 1, 24-57. https://doi.org/10.1162/CPSY_a_00002.