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mgc: Multiscale Graph Correlation

Multiscale Graph Correlation (MGC) is a framework developed by Vogelstein et al. (2019) <doi:10.7554/eLife.41690> 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.

Version: 2.0.2
Depends: R (≥ 3.4.0)
Imports: stats, MASS, abind, boot, energy, raster
Suggests: testthat (≥ 2.1.0), ggplot2, reshape2, knitr, rmarkdown
Published: 2020-06-23
DOI: 10.32614/CRAN.package.mgc
Author: Eric Bridgeford [aut, cre], Censheng Shen [aut], Shangsi Wang [aut], Joshua Vogelstein [ths]
Maintainer: Eric Bridgeford <ericwb95 at gmail.com>
License: GPL-2
URL: https://github.com/neurodata/r-mgc
NeedsCompilation: yes
CRAN checks: mgc results

Documentation:

Reference manual: mgc.pdf
Vignettes: discriminability
mgc
class_sims
reg_sims

Downloads:

Package source: mgc_2.0.2.tar.gz
Windows binaries: r-devel: mgc_2.0.2.zip, r-release: mgc_2.0.2.zip, r-oldrel: mgc_2.0.2.zip
macOS binaries: r-release (arm64): mgc_2.0.2.tgz, r-oldrel (arm64): mgc_2.0.2.tgz, r-release (x86_64): mgc_2.0.2.tgz, r-oldrel (x86_64): mgc_2.0.2.tgz
Old sources: mgc archive

Reverse dependencies:

Reverse imports: coveR2, mineSweepR

Linking:

Please use the canonical form https://CRAN.R-project.org/package=mgc to link to this page.

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.