parcor-package {parcor}R Documentation

Parcor: Estimation of partial correlations based on regularized regression.

Description

This package contains different methods to estimate the matrix of partial correlations based on a (n x p) matrix X. For p>n, the matrix of partial correlations can be estimated based on p least-squares regression fits. However, for p<n, theses least-squares problems are ill-posed and need to be regularized. This package contains four different regularized regression techniques for the estimation of the partial correlations: lasso, adaptive lasso, ridge regression, and partial least squares.

Details

Package: parcor
Type: Package
Version: 0.1
Date: 2009-04-22
License: GPL2 or newer
LazyLoad: yes

Author(s)

Nicole Kraemer, Juliane Schaefer

Maintainer: Nicole Kraemer <nkraemer@cs.tu-berlin.de>

References

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

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


[Package parcor version 0.1 Index]