enetLTS objectDoes k-fold cross-validation for enetLTS, produces a plot,
and returns optimal values for alpha and lambda.
cv.enetLTS(index=NULL,xx,yy,family,h,alphas,lambdas,nfold,repl,ncores,plot=TRUE)A user supplied index. The default is NULL.
matrix xx as in enetLTS.
response yy as in enetLTS.
a description of the error distribution and link function to be used
in the model. "gaussian" and "binomial" options are available.
a user supplied numeric value giving how many observations will be used.
a user supplied alpha sequence for the elastic net penalty, which is the mixing proportion of the ridge and lasso penalties and takes value in [0,1]. Here \(\alpha=1\) is the lasso penalty, and \(\alpha=0\) the ridge penalty.
a user supplied lambda sequence for the strength of the elastic net penalty.
a user supplied numeric value for fold number of k-fold cross-validation which used in varied functions of the algorithm. The default is 5-fold cross-validation.
a user supplied posiitive number for more stable results, repeat the k-fold CV
repl times and take the average of the corresponding evaluation measure. The default is 5.
a positive integer giving the number of processor cores to be used for parallel computing. The default is 4.
a logical indicating if produces a plot for k-fold cross-validation based on alpha and lambda combinations. The default is TRUE.
produces a plot,
and returns optimal values for alpha and lambda