R: MGC Local Correlations

mgc.localcorr

R Documentation

MGC Local Correlations

Description

Compute all local correlation coefficients in O(n^2 log n)

Usage

mgc.localcorr(
  X,
  Y,
  is.dist.X = FALSE,
  dist.xfm.X = mgc.distance,
  dist.params.X = list(method = "euclidean"),
  dist.return.X = NULL,
  is.dist.Y = FALSE,
  dist.xfm.Y = mgc.distance,
  dist.params.Y = list(method = "euclidean"),
  dist.return.Y = NULL,
  option = "mgc"
)

Arguments

`X`	is interpreted as: a `[n x d]` data matrix X is a data matrix with `n` samples in `d` dimensions, if flag `is.dist.X=FALSE`. a `[n x n]` distance matrix X is a distance matrix. Use flag `is.dist.X=TRUE`.
`Y`	is interpreted as: a `[n x d]` data matrix Y is a data matrix with `n` samples in `d` dimensions, if flag `is.dist.Y=FALSE`. a `[n x n]` distance matrix Y is a distance matrix. Use flag `is.dist.Y=TRUE`.
`is.dist.X`	a boolean indicating whether your `X` input is a distance matrix or not. Defaults to `FALSE`.
`dist.xfm.X`	if `is.dist == FALSE`, a distance function to transform `X`. If a distance function is passed, it should accept an `[n x d]` matrix of `n` samples in `d` dimensions and return a `[n x n]` distance matrix as the `$D` return argument. See mgc.distance for details.
`dist.params.X`	a list of trailing arguments to pass to the distance function specified in `dist.xfm.X`. Defaults to `list(method='euclidean')`.
`dist.return.X`	the return argument for the specified `dist.xfm.X` containing the distance matrix. Defaults to `FALSE`. `is.null(dist.return)` use the return argument directly from `dist.xfm` as the distance matrix. Should be a `[n x n]` matrix. `is.character(dist.return) \| is.integer(dist.return)` use `dist.xfm.X[[dist.return]]` as the distance matrix. Should be a `[n x n]` matrix.
`is.dist.Y`	a boolean indicating whether your `Y` input is a distance matrix or not. Defaults to `FALSE`.
`dist.xfm.Y`	if `is.dist == FALSE`, a distance function to transform `Y`. If a distance function is passed, it should accept an `[n x d]` matrix of `n` samples in `d` dimensions and return a `[n x n]` distance matrix as the `dist.return.Y` return argument. See mgc.distance for details.
`dist.params.Y`	a list of trailing arguments to pass to the distance function specified in `dist.xfm.Y`. Defaults to `list(method='euclidean')`.
`dist.return.Y`	the return argument for the specified `dist.xfm.Y` containing the distance matrix. Defaults to `FALSE`. `is.null(dist.return)` use the return argument directly from `dist.xfm.Y(Y)` as the distance matrix. Should be a `[n x n]` matrix. `is.character(dist.return) \| is.integer(dist.return)` use `dist.xfm.Y(Y)[[dist.return]]` as the distance matrix. Should be a `[n x n]` 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.

Value

A list contains the following:

`corr`	consists of all local correlations within [-1,1] by double matrix index
`varX`	contains all local variances for X.
`varY`	contains all local variances for X.

Author(s)

C. Shen

Examples

library(mgc)

n=200; d=2
data <- mgc.sims.linear(n, d)
lcor <- mgc.localcorr(data$X, data$Y)