Description Usage Arguments Value Note Author(s) See Also Examples
Split observations or groups of observations into K folds to be used for (repeated) K-fold cross-validation. K should thereby be chosen such that all folds are of approximately equal size.
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n |
an integer giving the number of observations to be split into
folds. This is ignored if |
K |
an integer giving the number of folds into which the observations
should be split (the default is five). Setting |
R |
an integer giving the number of replications for repeated K-fold cross-validation. This is ignored for for leave-one-out cross-validation and other non-random splits of the data. |
type |
a character string specifying the type of folds to be
generated. Possible values are |
grouping |
a factor specifying groups of observations. If supplied, the data are split according to the groups rather than individual observations such that all observations within a group belong to the same fold. |
An object of class "cvFolds"
with the following components:
n
an integer giving the number of observations or groups.
K
an integer giving the number of folds.
R
an integer giving the number of replications.
subsets
an integer matrix in which each column contains a permutation of the indices of the observations or groups.
which
an integer vector giving the fold for each permuted observation or group.
grouping
a list giving the indices of the observations belonging to each group. This is only returned if a grouping factor has been supplied.
This is a simple wrapper function for perrySplits
with a
control object generated by foldControl
.
Andreas Alfons
perrySplits
, foldControl
,
randomSplits
, bootSamples
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