Description Usage Arguments Value Author(s) See Also Examples

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).

1 | ```
splitControl(m, R = 1, grouping = NULL)
``` |

`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. |

An object of class `"splitControl"`

with the following
components:

`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`

if 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.

Andreas Alfons

`perrySplits`

, `randomSplits`

,
`foldControl`

, `bootControl`

1 2 3 | ```
set.seed(1234) # set seed for reproducibility
perrySplits(20, splitControl(m = 5))
perrySplits(20, splitControl(m = 5, R = 10))
``` |

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