mgc.sample: MGC Sample

Description Usage Arguments Value Author(s) Examples

View source: R/MGCSampleStat.R

Description

The main function that computes the MGC measure between two datasets: It first computes all local correlations, then use the maximal statistic among all local correlations based on thresholding.

Usage

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mgc.sample(A, B, option = "mgc")

Arguments

A

is interpreted as:

a [n x n] distance matrix

A is a square matrix with zeros on diagonal for n samples.

a [n x d] data matrix

A is a data matrix with n samples in d dimensions.

B

is interpreted as:

a [n x n] distance matrix

B is a square matrix with zeros on diagonal for n samples.

a [n x d] data matrix

B is a data matrix with n samples in d dimensions.

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 containing the following:

statMGC

is the sample MGC statistic within [-1,1]

localCorr

consists of all local correlations by double matrix index

optimalScale

the estimated optimal scale in matrix single index.

Author(s)

C. Shen

Examples

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library(mgc)

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

neurodata/mgc-r documentation built on Feb. 3, 2019, 12:43 a.m.