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Welcome to knockpy's documentation!
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Knockoffs are a powerful tool which can be used in combination with nearly any machine learning algorithm to control the false discovery rate (FDR) in feature selection. Knockoffs were initially developed in `Barber and Candes 2015`_ and `Candes et al 2018`_.

.. _Candes et al 2018: https://arxiv.org/abs/1610.02351
.. _Barber and Candes 2015: https://projecteuclid.org/download/pdfview_1/euclid.aos/1438606853

Knockpy is a python implementation of the knockoffs framework which makes it easy to apply knockoff-based inference in only a few lines of code. Knockpy is also built to be modular, so researchers and analysts can easily layer functionality on top of it. See usage for more details!

.. toctree::
   :maxdepth: 3
   :caption: Contents:

   installation
   usage
   mrcknock
   apiref


Indices and tables
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* :ref:`genindex`
* :ref:`modindex`
* :ref:`search`