{ "info": { "author": "hBayesDM Developers", "author_email": "hbayesdm-users@googlegroups.com", "bugtrack_url": null, "classifiers": [ "Environment :: Console", "Intended Audience :: Developers", "Intended Audience :: Science/Research", "License :: OSI Approved :: GNU General Public License v3 (GPLv3)", "Operating System :: OS Independent", "Programming Language :: Python", "Programming Language :: Python :: 3", "Programming Language :: Python :: 3.5", "Programming Language :: Python :: 3.6", "Programming Language :: Python :: 3.7", "Topic :: Scientific/Engineering" ], "description": "hBayesDM\n========\n\nThis is the Python version of *hBayesDM* (hierarchical Bayesian modeling of\nDecision-Making tasks), a user-friendly package that offers hierarchical\nBayesian analysis of various computational models on an array of\ndecision-making tasks. *hBayesDM* in Python uses `PyStan`_ (Python interface for\n`Stan`_) for Bayesian inference.\n\n.. _PyStan: https://github.com/stan-dev/pystan\n.. _Stan: http://mc-stan.org/\n\nIt supports Python 3.5 or higher versions and requires several packages including:\n`NumPy`_, `SciPy`_, `Pandas`_, `PyStan`_, `Matplotlib`_, and `ArviZ`_.\n\n.. _NumPy: https://www.numpy.org/\n.. _SciPy: https://www.scipy.org/\n.. _Pandas: https://pandas.pydata.org/\n.. _Matplotlib: https://matplotlib.org/\n.. _ArviZ: https://arviz-devs.github.io/arviz/\n\n- **Documentation**: http://hbayesdm.readthedocs.io/\n\nInstallation\n------------\n\nYou can install hBayesDM from PyPI with the following line:\n\n.. code:: bash\n\n pip install hbayesdm # Install using pip\n\nIf you want to install from source (by cloning from GitHub):\n\n.. code:: bash\n\n git clone https://github.com/CCS-Lab/hBayesDM.git\n cd hBayesDM\n cd Python\n\n python setup.py install # Install from source\n\nCitation\n--------\n\nIf you used hBayesDM or some of its codes for your research, please cite `this paper`_:\n\n.. _this paper: 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