| splitControl {perry} | R Documentation |
Control object for random data splits
Description
Generate an object that controls how to split n observations or
groups of observations into training and test data to be used for (repeated)
random splitting (also known as random subsampling or Monte Carlo
cross-validation).
Usage
splitControl(m, R = 1, grouping = NULL)
Arguments
m |
an integer giving the number of observations or groups of observations to be used as test data. |
R |
an integer giving the number of random data splits. |
grouping |
a factor specifying groups of observations. |
Value
An object of class "splitControl" with the following
components:
man integer giving the number of observations or groups of observations to be used as test data.
Ran integer giving the number of random data splits.
groupingif supplied, a factor specifying groups of observations. The data will then be split according to the groups rather than individual observations such that all observations within a group belong either to the training or test data.
Author(s)
Andreas Alfons
See Also
perrySplits, randomSplits,
foldControl, bootControl
Examples
set.seed(1234) # set seed for reproducibility
perrySplits(20, splitControl(m = 5))
perrySplits(20, splitControl(m = 5, R = 10))