Description Usage Arguments Details Value Author(s) References See Also Examples
Computes the list of the adjacency matrices in terms of the scale of the wavelet decomposition.
1 2 3 | 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.var.ind |
object of class |
n.ind |
number of individuals to take into account in the test. Only used with |
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. |
proc.length |
specifies the length of the original processes using to construct the |
use.tanh |
logical. If FALSE take the |
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.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 | 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)
}
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