Description Usage Arguments Details Value Author(s) See Also Examples
corr.matrix
calculates the correlation between all column pairs of a
given data frame, and thresholds the resultant correlation matrix based on a
given density (e.g., 0.1
if you want to keep only the 10% strongest
correlations). If you want to threshold by a specific correlation coefficient
(via the thresholds
argument), then the densities
argument is
ignored.
1  corr.matrix(resids, densities, thresholds = NULL, exclusions = NULL, ...)

resids 
Data table of the residuals (from 
densities 
Numeric vector indicating the resultant network density(ies); keeps the top X% of correlations 
thresholds 
Numeric; absolute correlation value to threshold by (default:

exclusions 
Numeric vector of indices (columns) to exclude (default:

... 
Other arguments, passed to 
If you wish to exclude regions from your analysis, you can give the indices
of their columns with the exclusions
argument.
By default, the Pearson correlation coefficients are calculated, but you can return Spearman by passing an additional argument.
A list with the following components:
R 
Numeric matrix of correlation coefficients. 
P 
Numeric matrix of pvalues. 
r.thresh 
A 3d binary array indicating correlations that are above a certain threshold. The length of the 3rd dimension equals the number of thresholds/densities supplied. 
thresholds 
Numeric vector; the thresholds supplied. 
densities 
Numeric vector; the densities supplied. 
Christopher G. Watson, [email protected]
Other Structural covariance network functions: IndividualContributions
,
brainGraph_boot
,
brainGraph_init
,
brainGraph_permute
,
get.resid
,
plot.brainGraph_resids
,
plot_volumetric
1 2 3 4 5  ## Not run:
corrs < lapply(groups, function(x) lapply(densities, function(y)
corr.matrix(resids.all[x], densities=y)))
## End(Not run)

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