dcor: Distance correlation and energy statistics in Python
Entity
UAM. Departamento de MatemáticasPublisher
ElsevierDate
2023-05-01Citation
10.1016/j.softx.2023.101326
SoftwareX 22 (2023): 101326
ISSN
2352-7110 (online)DOI
10.1016/j.softx.2023.101326Funded by
PID2019-106827GB-I00, PID2019-106827GB-I00Project
Gobierno de España. PID2019–106827GB-I00; Gobierno de España. PID2019-109387GB-I00Editor's Version
https://doi.org/10.1016/j.softx.2023.101326Subjects
Hypothesis testing; High Level languages; Vectorization; Distance Correlation; MatemáticasRights
© 2023 The AuthorsAbstract
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.
Files in this item
Google Scholar:Ramos Carreño, Carlos
-
Torrecilla Noguerales, José Luis
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