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updated docs
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rmj3197 committed Jun 4, 2024
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10 changes: 5 additions & 5 deletions README.rst
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.. _Black: https://github.com/psf/black

Introduction
=============
==============

The QuadratiK package is implemented in both **R** and **Python**, providing a comprehensive set of goodness-of-fit tests and a clustering technique using kernel-based quadratic distances. This framework aims to bridge the gap between the statistical and machine learning literatures. It includes:

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pip install -e .
Contributing Guide
"""""""""""""""""""""
^^^^^^^^^^^^^^^^^^^^^

Please refer to the `Contributing Guide <https://quadratik.readthedocs.io/en/latest/development/CONTRIBUTING.html>`_.

Code of Conduct
"""""""""""""""""
^^^^^^^^^^^^^^^^^

The code of conduct can be found at `Code of Conduct <https://quadratik.readthedocs.io/en/latest/development/CODE_OF_CONDUCT.html>`_.

License
"""""""""
^^^^^^^^^

This project uses the GPL-3.0 license, with a full version of the license included in the repository `here <https://github.com/rmj3197/QuadratiK/blob/master/LICENSE>`_.

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The work has been supported by Kaleida Health Foundation, Food and Drug Administration, and Department of Biostatistics, University at Buffalo.

References
-------------
------------
Saraceno G., Markatou M., Mukhopadhyay R., Golzy M. (2024).
Goodness-of-Fit and Clustering of Spherical Data: the QuadratiK package in R and Python. arXiv preprint arXiv:2402.02290.

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12 changes: 12 additions & 0 deletions doc/source/index.rst
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.. include:: ../../README.rst

===========================================
Package Documentation and Usage Examples
===========================================

.. toctree::
:hidden:
:maxdepth: 4
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user_guide/index.rst

================
Development
================

.. toctree::
:hidden:
:maxdepth: 4
:titlesonly:

development/index.rst

================
Changelog
================

.. toctree::
:hidden:
:maxdepth: 4
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