Description Usage Arguments Details Value See Also
Multidimensional crossvalidated estimation of the empirical risk for hyperparameter selection,
for an object of class FDboostLSS
setting the folds per default to resampling curves.
1 2 3 4 
object 
an object of class 
folds 
a weight matrix a weight matrix with number of rows equal to the number of observations. The number of columns corresponds to the number of crossvalidation runs, defaults to 25 bootstrap samples, resampling whole curves 
grid 
defaults to a grid up to the current number of boosting iterations.
The default generates the grid according to the defaults of

papply 
(parallel) apply function, defaults to 
trace 
print status information during crossvalidation? Defaults to 
fun 
if 
... 
additional arguments passed to 
The function cvrisk.FDboostLSS
is a wrapper for
cvrisk.mboostLSS
in package gamboostLSS.
It overrieds the default for the folds, so that the folds are sampled on the level of curves
(not on the level of single observations, which does not make sense for functional response).
An object of class cvriskLSS
(when fun
was not specified),
basically a matrix containing estimates of the empirical risk for a varying number
of bootstrap iterations. plot
and print
methods are available as well as an
mstop
method, see cvrisk.mboostLSS
.
cvrisk.mboostLSS
in packge gamboostLSS.
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