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 |
| Reference manual: | mgc.pdf |
| Vignettes: |
discriminability mgc class_sims reg_sims |
| 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 imports: | coveR2, mineSweepR |
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