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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.
github.com/neurodata/r-mgc |
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