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Compcors the input matrix using SVD and returns the result.
compcorr_nuisance<-compcor( fmri, mask, ncompcor=4, variance_extreme=0.975, returnhighvarmat=F, returnv=F )
input fmri image or matrix
returns the singular vectors in v-space
returns the high variance matrix on which svd is performed
dataframe is output
# NOT RUN { mat <- matrix( rnorm(50000) ,ncol=500) compcorrdf<-compcor( mat ) # }
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