This function computes the matrix of partial correlations via an estimation of the corresponding regression models via Partial Least Squares.
1 |
X |
matrix of observations. The rows of |
scale |
Scale the columns of X? Default is scale=TRUE. |
k |
Number of splits in |
ncomp |
Maximal number of components. Default is 15. |
verbose |
Print information on conflicting signs etc. Default is |
For each of the columns of X
, a regression model based on
Partial Least Squares is computed. The optimal model is determined via
cross-validation. The results of the regression models are
transformed via the function Beta2parcor
.
pcor |
estimated matrix of partial correlation coefficients. |
m |
optimal number of components for each of the |
Nicole Kraemer
N. Kraemer, J. Schaefer, A.-L. Boulesteix (2009) "Regularized Estimation of Large-Scale Gene Regulatory Networks using Gaussian Graphical Models", BMC Bioinformatics, 10:384
http://www.biomedcentral.com/1471-2105/10/384/
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