Does k-fold cross-validation for ccglmreg, produces a plot,
and returns cross-validated log-likelihood values for lambda
# S3 method for formula
cv.ccglmreg(formula, data, weights, offset=NULL, ...)
# S3 method for matrix
cv.ccglmreg(x, y, weights, offset=NULL, ...)
# S3 method for default
cv.ccglmreg(x, ...)
# S3 method for cv.ccglmreg
plot(x,se=TRUE,ylab=NULL, main=NULL, width=0.02, col="darkgrey", ...)
# S3 method for cv.ccglmreg
coef(object,which=object$lambda.which, ...)symbolic description of the model, see details.
argument controlling formula processing
via model.frame.
x matrix as in ccglmreg. It could be object of cv.ccglmreg.
response y as in ccglmreg.
Observation weights; defaults to 1 per observation
Not implemented yet
object of cv.ccglmreg
Indices of the penalty parameter lambda at which
estimates are extracted. By default, the one which generates the optimal cross-validation value.
logical value, if TRUE, standard error curve is also plotted
ylab on y-axis
title of plot
width of lines
color of standard error curve
Other arguments that can be passed to ccglmreg.
an object of class "cv.ccglmreg" is returned, which is a
list with the ingredients of the cross-validation fit.
a fitted ccglmreg object for the full data.
matrix of log-likelihood values with row values for lambda and column values for kth cross-validation
matrix of BIC values with row values for lambda and column values for kth cross-validation
The mean cross-validated log-likelihood values - a vector of length
length(lambda).
estimate of standard error of cv.
an optional vector of values between 1 and nfold
identifying what fold each observation is in.
a vector of lambda values
index of lambda that gives minimum cv value.
value of lambda that gives minimum cv value.
The function runs ccglmreg nfolds+1 times; the
first to compute the lambda sequence, and then to
compute the fit with each of the folds omitted. The error or the loss value is
accumulated, and the average value and standard deviation over the
folds is computed. Note that cv.ccglmreg can be used to search for
values for alpha: it is required to call cv.ccglmreg with a fixed vector foldid for different values of alpha.
Zhu Wang (2020) Unified Robust Estimation via the COCO, arXiv e-prints, https://arxiv.org/abs/2010.02848
ccglmreg and plot, predict, and coef methods for "cv.ccglmreg" object.