STATINF
=======

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   :target: https://pepy.tech/project/statinf
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   :target: https://pypi.org/project/statinf/
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    :target: https://github.com/florianfelice/statinf

This library aims at re-implementing standard statistical tools (such as OLS, logistic regression, Neural Network) and is built on top of `numpy`_
for handling data and `jax`_ for differential computing.
The objective is to implement new methodologies from research projects on these models.
The library also provides a data generator for linear and binary data.


The library is pip-installable and the source code is available on my `Git <https://github.com/florianfelice/statinf>`_.
For any question or suggestion of improvement, please `contact me <mailto:florian.website.mail@gmail.com>`_.


Installation
============

You can get STATINF from `PyPI <https://pypi.org/project/statinf/>`_ with:

.. code-block:: console

   pip install statinf

The library is supported on Windows, Linux and MacOS.

STATINF tries to use the least number of dependencies possible:

* `pandas <https://pandas.pydata.org/>`_: used to convert data frames into arrays.
* `numpy`_ : main library for data handling and matrix operations.
* `scipy <https://www.scipy.org/>`_: probability density functions.
* `jax`_: matrix operations and back-propagation for Deep Learning models.
* `matplotlib <https://matplotlib.org/>`_: plots of training performances.
* `pycof <https://www.florianfelice.com/pycof?orgn=statinf>`_: basic information printing.

Once your dependencies are installed, you may need additional steps to enable GPUs (if eligible), see `FAQ <updates/faq.html?orgn=stating_idx#why-is-my-gpu-not-recognized>`_.


Indices and tables
==================

* :ref:`genindex`
* :ref:`modindex`
* :ref:`search`



Modules available
=================

Distributions
-------------

.. toctree::

    distributions/discrete

Econometrics
------------

.. toctree::

    econometrics/ols
    econometrics/glm


Statistics
----------

.. toctree::

    stats/descriptive
    stats/tests
    stats/timeseries
    stats/bayesian
    stats/unsupervised
    stats/nonparametrics


Machine Learning
----------------

.. toctree::

    ml/performance


Deep Learning
-------------

.. toctree::

    deeplearning/neuralnetwork
    deeplearning/activations
    deeplearning/optimizers
    deeplearning/losses
    deeplearning/initializations
    deeplearning/example


Data
----

.. toctree::

    data/generate
    data/process


Release and FAQ
===============

.. toctree::

   updates/release
   updates/faq


.. _numpy: https://numpy.org/
.. _jax: https://jax.readthedocs.io