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