dcor: Distance correlation and energy statistics in Python']Python

被引:8
|
作者
Ramos-Carreno, Carlos [1 ]
Torrecilla, Jose L. [2 ]
机构
[1] Univ Autonoma Madrid, Escuela Politecn Super, Dept Comp Sci, Madrid, Spain
[2] Univ Autonoma Madrid, Fac Ciencias, Dept Math, Madrid, Spain
关键词
Energy statistics; Energy distance; Distance correlation; Hypothesis testing; !text type='Python']Python[!/text; VARIABLE SELECTION;
D O I
10.1016/j.softx.2023.101326
中图分类号
TP31 [计算机软件];
学科分类号
081202 ; 0835 ;
摘要
This article presents dcor, an open-source Python package dedicated to distance correlation and other statistics related to energy distance. These energy statistics include distances between distributions and the associated tests for homogeneity and independence. Some of the most efficient algorithms for the estimation of these measures have been implemented relying on optimization techniques such as vectorization, compilation, and parallelization. The performance of these estimators is evaluated by comparison with alternative implementations in other packages. The package is also designed to be compatible with the packages conforming the scientific Python ecosystem. With that purpose in mind, dcor is an early adopter of the Python array API standard.(c) 2023 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
引用
收藏
页数:7
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