Description Usage Arguments Details Value Author(s) References See Also Examples
Computes the p-values for all the entries in the matrix test.mat
using the asymtotic properties of the estimator of the wavelet correlation given in (Whitcher, 2000).
1 2 | p.value.compute(test.mat, var.ind.mat = 0, n.ind = 0, test.method = "gaussian",
proc.length, sup, num.levels, use.tanh = FALSE)
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test.mat |
matrix containing the wavelet correlation to be tested |
var.ind.mat |
matrix containing the variance inter individuals of the correlation. Only used with |
n.ind |
number of individuals to take into account in the test. Only used with |
test.method |
name of the method to be applied. |
proc.length |
specifies the length of the original processes using to construct the |
num.levels |
specifies the number of the wavelet scale to take into account in the hypothesis test. Only used with |
use.tanh |
logical. If FALSE take the |
sup |
indicates the correlation threshold to consider in each hypothesis test. |
Each hypothesis test is written as :
H_0 : "|correlation| <= sup"
H_1 : "|correlation| > sup"
This function is essentially an internal function called by const.adj.mat
.
Vector with the p-value for each entry of the matrix.
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.
codeconst.adj.mat
1 2 3 4 5 6 7 8 9 10 11 12 13 14 | 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 = 4,
boundary = "periodic", p.corr = 0.975)
# For scale 4
pvalue.cor<-p.value.compute(wave.cor.list[[4]],proc.length=dim(brain)[1], sup=0.44,
num.levels=4)
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