const.adj.list {brainwaver} | R Documentation |
Computes the list of the adjacency matrices in terms of the scale of the wavelet decomposition.
const.adj.list(wave.cor.list, wave.var.ind = 0, n.ind = 0, thresh = 0.05, sup = 0, test.method = "gaussian", proc.length, use.tanh = FALSE)
wave.cor.list |
object of class "Wave Correlation" containing the correlation matrices to be analysed |
wave.var.ind |
object of class "Wave Correlation" containing the inter individuals variance 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 wave.cor.list |
use.tanh |
logical. If FALSE take the atanh of the correlation values before applying the hypothesis test, in order to use the Fisher approximation |
Each hypothesis test is written as :
H_0 : "|correlation| <= sup"
H_1 : "|correlation| > sup"
Object of class "Wave Adjacency matrix"
, basically, a list with the following
components
d? |
Adjacency matrix for each scale of the wavelet decomposition |
S. Achard
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.
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 matrices associated to each level of the # wavelet decomposition wave.adj.list<-const.adj.list(wave.cor.list, sup = 0.44, proc.length=dim(brain)[1]) par(mfrow=c(3,2)) for(i in 1:4) { name.txt<-paste("Level ",i,sep="") image(wave.adj.list[[i]],col=gray((0:20)/20),main=name.txt) }