mgc.dist.xfm: MGC Distance Transform
In neurodata/r-mgc: Multiscale Graph Correlation

Description Usage Arguments Value Author(s) Examples

Transform the distance matrices, with column-wise ranking if needed.

1	mgc.dist.xfm(X, Y, option = "mgc", optionRk = TRUE)

`X`	`[nxn]` is a distance matrix
`Y`	`[nxn]` is a second distance matrix
`option`	is a string that specifies which global correlation to build up-on. Defaults to `mgc`. `'mgc'` use the MGC global correlation. `'dcor'` use the dcor global correlation. `'mantel'` use the mantel global correlation. `'rank'` use the rank global correlation.
`optionRk`	is a string that specifies whether ranking within column is computed or not. If `option='rank'`, ranking will be performed regardless of the value specified by `optionRk`. Defaults to `TRUE`.

A list containing the following:

`A`	`[nxn]` the centered distance matrix for X.
`B`	`[nxn]` the centered distance matrix for Y.
`RX`	`[nxn]` the column-rank matrices of X.
`RY`	`[nxn]` the column-rank matrices of Y.

C. Shen

library(mgc)

n=200; d=2
data <- mgc.sims.linear(n, d)
Dx <- as.matrix(dist(data$X), nrow=n); Dy <- as.matrix(dist(data$Y), nrow=n)
dt <- mgc.dist.xfm(Dx, Dy)