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Hierarchical Bayesian modeling of RLDM tasks, using R & Python

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hBayesDM

Project Status: Active – The project has reached a stable, usable state and is being actively developed. Build Status CRAN Latest Release Downloads DOI

hBayesDM (hierarchical Bayesian modeling of Decision-Making tasks) is a user-friendly package that offers hierarchical Bayesian analysis of various computational models on an array of decision-making tasks. hBayesDM uses Stan for Bayesian inference.

Now, hBayesDM supports both R and Python!

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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},
}

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We thank HuaFeng Lu who designed and donated the logo for the hBayesDM package.

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Hierarchical Bayesian modeling of RLDM tasks, using R & Python

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  • Python 53.1%
  • R 24.9%
  • Stan 19.4%
  • CSS 1.6%
  • JavaScript 0.5%
  • Shell 0.2%
  • Other 0.3%