Description Usage Arguments Details Author(s) See Also

Generic function to estimate the prediction error of a fitted model via
(repeated) *K*-fold cross-validation, (repeated) random splitting (also
known as random subsampling or Monte Carlo cross-validation), or the
bootstrap.

1 |

`object` |
the fitted model for which to estimate the prediction error. |

`...` |
additional arguments to be passed down to methods. |

The idea is that developers write easy-to-use methods for end users to
leverage the prediction error estimation framework for their models. A
typical `perry`

method consists of the following two parts: first the
data are extracted from the model, then function `perryFit`

is
called to perform prediction error estimation. The programming effort of
implementing prediction error estimation for a certain model is thus greatly
reduced.

Examples for methods are available in package perryExamples (see
`perry-methods`

).

Andreas Alfons

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