CalcAVG {evolqg} | R Documentation |
Calculates mean correlations within- and between-modules
Description
Uses a binary correlation matrix as a mask to calculate average within- and between-module correlations. Also calculates the ratio between them and the Modularity Hypothesis Index.
Usage
CalcAVG(cor.hypothesis, cor.matrix, MHI = TRUE, landmark.dim = NULL)
Arguments
cor.hypothesis |
Hypothetical correlation matrix, with 1s within-modules and 0s between modules |
cor.matrix |
Observed empirical correlation matrix. |
MHI |
Indicates if Modularity Hypothesis Index should be calculated instead of AVG Ratio. |
landmark.dim |
Used if within-landmark correlations are to be excluded in geometric morphometric data. Either 2 for 2d data or 3 for 3d data. Default is NULL for non geometric morphomotric data. |
Value
a named vector with the mean correlations and derived statistics
Examples
# Module vectors
modules = matrix(c(rep(c(1, 0, 0), each = 5),
rep(c(0, 1, 0), each = 5),
rep(c(0, 0, 1), each = 5)), 15)
# Binary modular matrix
cor.hypot = CreateHypotMatrix(modules)[[4]]
# Modular correlation matrix
hypot.mask = matrix(as.logical(cor.hypot), 15, 15)
mod.cor = matrix(NA, 15, 15)
mod.cor[ hypot.mask] = runif(length(mod.cor[ hypot.mask]), 0.8, 0.9) # within-modules
mod.cor[!hypot.mask] = runif(length(mod.cor[!hypot.mask]), 0.3, 0.4) # between-modules
diag(mod.cor) = 1
mod.cor = (mod.cor + t(mod.cor))/2 # correlation matrices should be symmetric
CalcAVG(cor.hypot, mod.cor)
CalcAVG(cor.hypot, mod.cor, MHI = TRUE)
[Package evolqg version 0.3-4 Index]