parcor (version 0.2-6)

# adalasso.net: Partial Correlations with (Adaptive) Lasso

## Description

This function computes the matrix of partial correlations based on an estimation of the corresponding regression models via lasso and adaptive lasso respectively.

## Usage

`adalasso.net(X, k = 10,use.Gram=FALSE,both=TRUE,verbose=FALSE,intercept=TRUE)`

## Arguments

X
matrix of observations. The rows of `X` contain the samples, the columns of `X` contain the observed variables.
k
the number of splits in `k`-fold cross-validation. The same `k` is used for the estimation of the weights and the estimation of the penalty term for adaptive lasso. Default value is `k`=10.
use.Gram
When the number of variables is very large, you may not want LARS to precompute the Gram matrix. Default is `use.Gram`=FALSE.
both
Logical. If both=FALSE, only the lasso solution is computed. Default is both=TRUE.
verbose
Print information on conflicting signs etc. Default is `verbose=FALSE`
intercept
Should an intercept be included in the regression models? Default is `intercept=TRUE`.

## Value

pcor.adalasso
estimated matrix of partial correlation coefficients for adaptive lasso.
pcor.lasso
estimated matrix of partial correlation coefficients for lasso.
...

## Details

For each of the columns of `X`, a regression model based on (adaptive) lasso is computed. In each of the `k`-fold cross-validation steps, the weights for adaptive lasso are computed in terms of a lasso fit. (The optimal value of the penalty term is selected via `k`-fold cross-validation). Note that this implies that a lasso solution is computed k*k times! Finally, the results of the regression models are transformed via the function `Beta2parcor`.

## References

H. Zou (2006) "The Adaptive Lasso and its Oracle Property", Journal of the American Statistical Association. 101 (476): 1418-1429.

N. Kraemer, J. Schaefer, A.-L. Boulesteix (2009) "Regularized Estimation of Large-Scale Gene Regulatory Networks using Gaussian Graphical Models", BMC Bioinformatics, 10:384

## See Also

`Beta2parcor`, `adalasso`

## Examples

Run this code
``````n<-20
p<-10
X<-matrix(rnorm(n*p),ncol=p)
pc<-adalasso.net(X,k=5)

``````

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