ridge.net {parcor}R Documentation

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.

Author(s)

Nicole Kraemer

References

N. Kraemer, J. Schaefer, A.-L. Boulesteix (2009) "Regularized Estimation of Large-Scale Gene Regulatory Networks using Gaussian Graphical Models", preprint

http://ml.cs.tu-berlin.de/~nkraemer/publications.html

See Also

ridge.cv

Examples

n<-50
p<-10
X<-matrix(rnorm(n*p),ncol=p)
pc<-ridge.net(X,k=5)

[Package parcor version 0.1 Index]