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.
- Changes to previous version:
Initial Announcement on mloss.org.
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