parcor (version 0.2-6)

ridge.net: Partial correlations with ridge regression.

Description

This function computes the matrix of partial correlations via an estimation of the corresponding regression models via Ridge Regression.

Usage

ridge.net(X, lambda, plot.it = FALSE, scale = TRUE, k = 10,verbose=FALSE)

Arguments

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

Value

pcor

estimated matrix of partial correlations.

lambda.opt

optimal value of lambda for each of the ncol regression models.

References

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/

See Also

ridge.cv

Examples

n<-20
p<-40
X<-matrix(rnorm(n*p),ncol=p)
pc<-ridge.net(X,k=5)