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Initial stats docs #15

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8 changes: 8 additions & 0 deletions docs/source/supported/stats.rst
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.. automodule:: numba-scipy.stats
:no-members:
:no-inherited-members:
:no-special-members:

.. toctree::
:hidden:

121 changes: 121 additions & 0 deletions numba_scipy/stats/__init__.py
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"""
==========================================
Statistical functions (:mod:`numba-scipy.stats`)
==========================================

.. currentmodule:: numba-scipy.stats

This module aims to provide the existing functionality in SciPy's stats_ module
This module contains a large number of probability distributions as
well as a growing library of statistical functions.

Each univariate distribution is an instance of a subclass of `rv_continuous`
(`rv_discrete` for discrete distributions):

.. _stats: https://docs.scipy.org/doc/scipy/reference/stats.html

.. autosummary::
:toctree: generated/

rv_continuous
rv_discrete
rv_histogram

Continuous distributions
========================

.. autosummary::
:toctree: generated/

norm -- Normal (Gaussian)

Multivariate distributions
==========================

.. autosummary::
:toctree: generated/


Discrete distributions
======================

.. autosummary::
:toctree: generated/


An overview of statistical functions is given below.


Summary statistics
==================

.. autosummary::
:toctree: generated/



Frequency statistics
====================


Correlation functions
=====================


Statistical tests
=================



Transformations
===============



Statistical distances
=====================



Random variate generation
=========================


Circular statistical functions
==============================



Contingency table functions
===========================


Plot-tests
==========



Masked statistics functions
===========================



Univariate and multivariate kernel density estimation
=====================================================



Warnings used in :mod:`scipy.stats`
===================================



"""


from .stats import *
from .distributions import *

__all__ = [s for s in dir() if not s.startswith("_")] # Remove dunders.
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@person142 person142 Sep 21, 2019

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This is a practice from SciPy that probably shouldn't be carried over-it tends to lead to all sorts of junk ending up in __all__. Better to define __all__ for stats and distributions and then combine them here.