Multiscale Graph Correlation

Multiscale Graph Correlation (MGC) is a framework developed by Shen et al. (2017) that extends global correlation procedures to be multiscale; consequently, MGC tests typically require far fewer samples than existing methods for a wide variety of dependence structures and dimensionalities, while maintaining computational efficiency. Moreover, MGC provides a simple and elegant multiscale characterization of the potentially complex latent geometry underlying the relationship.


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Reference manual

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install.packages("mgc")

1.0.1 by Eric Bridgeford, a year ago


https://github.com/neurodata/mgc


Browse source code at https://github.com/cran/mgc


Authors: Eric Bridgeford [aut, cre] , Censheng Shen [aut] , Shangsi Wang [aut] , Joshua Vogelstein [ths]


Documentation:   PDF Manual  


GPL-2 license


Imports stats, SDMTools, MASS

Suggests testthat, ggplot2, reshape2, knitr, rmarkdown


See at CRAN