mgc.localcorr: MGC Local Correlations

In mgc: Multiscale Graph Correlation

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)

mgc documentation built on July 1, 2020, 7:09 p.m.