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Python interface for hBayesDM, hierarchical Bayesian modeling of RL-DM tasks

Project description

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.

Installation

You can install hBayesDM from PyPI with the following line:

pip install hbayesdm  # Install using pip

If 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 source

Citation

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},
}

Project details


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hbayesdm-1.1.1.tar.gz (387.7 kB view hashes)

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