cvComGGL {ComGGL} | R Documentation |
The function performs K-fold CV to select the regularization parameters.
cvComGGL(Kfolds,Y,lambda1,lambda2,lambda3,K,pd,list.controls)
Kfolds |
The number of folds used for cross-validation; default is 3. |
Y |
Data matrix of dimension nxp. |
lambda1 |
Regularization parameter that dictates the sparsity of the undirected graphs |
lambda2 |
Regularization parameter that controls the grouping effect |
lambda3 |
Regularization parameter that controls the balance between |
K |
The number of desired communities of nodes; default is |
pd |
Indicator if |
list.controls |
List of control parameters specifying
|
A list containing the objects:
OptLamba_loglik |
Optimal triple |
OptLamba_tr |
Optimal triple |
Performance |
Loglikelihood loss and the Trace loss for all triplets. |
data(fmri) lambda1=c(.2,.4) lambda2=c(.1,.3) lambda3=c(1,2) obj=cvComGGL(3,Y,lambda1,lambda2,lambda3)