This release is a pre-release and may not be stable for production use.
This is the Python version of hBayesDM (hierarchical Bayesian modeling of Decision-Making tasks), a user-friendly package that offers hierarchical Bayesian analysis of various computational models on an array of decision-making tasks. hBayesDM in Python uses PyStan (Python interface for Stan) for Bayesian inference.
It supports Python 3.5 or higher versions and requires several packages including: NumPy, SciPy, Pandas, PyStan, Matplotlib, and ArviZ.
Documentation: http://hbayesdm.readthedocs.io/
Installation
You can install hBayesDM from PyPI with the following line:
pip install hbayesdm # Install using pipIf you want to install from source (by cloning from GitHub):
git clone https://github.com/CCS-Lab/hBayesDM.git
cd hBayesDM
cd Python
python setup.py install # Install from sourceCitation
If you used hBayesDM or some of its codes for your research, please cite this paper:
@article{hBayesDM,
title = {Revealing Neurocomputational Mechanisms of Reinforcement Learning and Decision-Making With the {hBayesDM} Package},
author = {Ahn, Woo-Young and Haines, Nathaniel and Zhang, Lei},
journal = {Computational Psychiatry},
year = {2017},
volume = {1},
pages = {24--57},
publisher = {MIT Press},
url = {doi:10.1162/CPSY_a_00002},
}2 maintainers
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