ridge.net {parcor} | R Documentation |
This function computes the matrix of partial correlations via an estimation of the corresponding regression models via Ridge Regression.
ridge.net(X, lambda, plot.it = FALSE, scale = TRUE, k = 10,verbose=FALSE)
X |
matrix of observations. The rows of X contain the
samples, the columns of X contain the observed variables. |
lambda |
Vector of penalty terms. |
scale |
Scale the columns of X? Default is scale=TRUE. |
k |
Number of splits in k -fold cross-validation. Default value is k =10. |
plot.it |
Plot the cross-validation error as a function of lambda ? Default is FALSE. |
verbose |
Print information on conflicting signs etc. Default is verbose=FALSE |
pcor |
estimated matrix of partial correlations. |
lambda.opt |
optimal value of lambda for each of the ncol regression models. |
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/
n<-20 p<-40 X<-matrix(rnorm(n*p),ncol=p) pc<-ridge.net(X,k=5)