const.adj.mat: Computation of the adjacency matrix

In brainwaver: Basic wavelet analysis of multivariate time series with a visualisation and parametrisation using graph theory.

Description

Computes the adjacency matrix for a given correlation matrix.

Usage

const.adj.mat(cor.mat, var.ind.mat = 0, n.ind = 0, thresh = 0.05, sup = 0, 
              test.method = "gaussian", proc.length, num.levels, 
              use.tanh = FALSE)

Arguments

cor.mat	matrix containing the correlation values. (must be diagonal with 1 on the diagonal)
var.ind.mat	matrix containing the variance inter individuals of the correlation. Only used with test.method="t.test". (default not used)
n.ind	number of individuals to take into account in the test. Only used with test.method="t.test". (default not used)
thresh	indicates the rate at which the FDR procedure is controlled. (default 0.05)
sup	indicates the correlation threshold to consider in each hypothesis test.
test.method	name of the method to be applied. "gaussian" assumes a gaussian law for the estimator. "t.test" implements a t.test for computing the p-value. (default "gaussian")
proc.length	specifies the length of the original processes using to construct the cor.mat
num.levels	specifies the number of the wavelet scale to take into account in the hypothesis test. Only used with test.method="gaussian"
use.tanh	logical. If FALSE take the atanh of the correlation values before applying the hypothesis test, in order to use the Fisher approximation

Details

Each hypothesis test is written as :

H_0 : "|correlation| <= sup"

H_1 : "|correlation| > sup"

Value

Binary matrix.

Author(s)

S. Achard

References

S. Achard, R. Salvador, B. Whitcher, J. Suckling, Ed Bullmore (2006) A Resilient, Low-Frequency, Small-World Human Brain Functional Network with Highly Connected Association Cortical Hubs. Journal of Neuroscience, Vol. 26, N. 1, pages 63-72.

See Also

const.adj.list

Examples

data(brain)
brain<-as.matrix(brain)
# WARNING : To process only the first five regions
brain<-brain[,1:5]


#Construction of the correlation matrices for each level of the wavelet decomposition
wave.cor.list<-const.cor.list(brain, method = "modwt" ,wf = "la8", n.levels = 6,
                               boundary = "periodic", p.corr = 0.975)

#Construction of the adjacency matrice for scale 4

adj.mat.4<-const.adj.mat(wave.cor.list[[4]], sup = 0.44,proc.length=dim(brain)[1], 
                          num.levels=4)

image(adj.mat.4,col=gray((0:20)/20))

Example output

Loading required package: waveslim

waveslim: Wavelet Method for 1/2/3D Signals (version = 1.7.5.1)

brainwaver documentation built on May 2, 2019, 10:23 a.m.