# encoding: utf-8

"""
dcor: distance correlation and energy statistics in Python.

E-statistics are functions of distances between statistical observations
in metric spaces.

Distance covariance and distance correlation are
dependency measures between random vectors introduced in [SRB07]_ with
a simple E-statistic estimator.

This package offers functions for calculating several E-statistics
such as:

- Estimator of the energy distance [SR13]_.
- Biased and unbiased estimators of distance covariance and
  distance correlation [SRB07]_.
- Estimators of the partial distance covariance and partial
  distance covariance [SR14]_.

It also provides tests based on these E-statistics:

- Test of homogeneity based on the energy distance.
- Test of independence based on distance covariance.

References
----------
.. [SR13] Gábor J. Székely and Maria L. Rizzo. Energy statistics: a class of
           statistics based on distances. Journal of Statistical Planning and
           Inference, 143(8):1249 – 1272, 2013.
           URL:
           http://www.sciencedirect.com/science/article/pii/S0378375813000633,
           doi:10.1016/j.jspi.2013.03.018.
.. [SR14]  Gábor J. Székely and Maria L. Rizzo. Partial distance correlation
           with methods for dissimilarities. The Annals of Statistics,
           42(6):2382–2412, 12 2014.
           doi:10.1214/14-AOS1255.
.. [SRB07] Gábor J. Székely, Maria L. Rizzo, and Nail K. Bakirov. Measuring and
           testing dependence by correlation of distances. The Annals of
           Statistics, 35(6):2769–2794, 12 2007.
           doi:10.1214/009053607000000505.

"""
import os
import pathlib

from setuptools import find_packages, setup

version = (
    pathlib.Path(os.path.dirname(__file__)) / 'dcor' / 'VERSION'
).read_text().strip()

setup(
    name="dcor",
    version=version,
    include_package_data=True,
    packages=find_packages(),
)
