mgc.stat.driver

is a string that specifies which global correlation to build up-on. Defaults to <code>'mgc'</code>.<dl class="dl-horizontal">
 <dt><code>'mgc'</code></dt><dd>use the MGC global correlation.</dd>
 <dt><code>'dcor'</code></dt><dd>use the dcor global correlation.</dd>
 <dt><code>'mantel'</code></dt><dd>use the mantel global correlation.</dd>
 <dt><code>'rank'</code></dt><dd>use the rank global correlation.</dd>
</dl>

option

MGC Sample Statistic Internal Driver

internal

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.

Eric Bridgeford

Multiscale Graph Correlation

Censheng Shen

Shangsi Wang

Joshua Vogelstein

mgc.stat.driver function

is a string that specifies which global correlation to build up-on. Defaults to <code>'mgc'</code>.<dl class='dl-horizontal'>
 <dt><code>'mgc'</code></dt><dd>use the MGC global correlation.</dd>
 <dt><code>'dcor'</code></dt><dd>use the dcor global correlation.</dd>
 <dt><code>'mantel'</code></dt><dd>use the mantel global correlation.</dd>
 <dt><code>'rank'</code></dt><dd>use the rank global correlation.</dd>
</dl>

mgc.stat.driver: MGC Sample Statistic Internal Driver

Description

Usage

Arguments