Description Usage Arguments Details Value Author(s) References See Also Examples

Two plots from Ridge regression are generated: The MSE resulting from Generalized Cross Validation (GCV) versus the Ridge parameter lambda, and the regression coefficients versus lambda. The optimal choice for lambda is indicated.

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`formula` |
formula, like y~X, i.e., dependent~response variables |

`data` |
data frame to be analyzed |

`lambda` |
possible values for the Ridge parameter to evaluate |

`...` |
additional plot arguments |

For all values provided in lambda the results for Ridge regression are computed.
The function `lm.ridge`

is used for cross-validation and
Ridge regression.

`predicted` |
predicted values for the optimal lambda |

`lambdaopt` |
optimal Ridge parameter lambda from GCV |

Peter Filzmoser <P.Filzmoser@tuwien.ac.at>

K. Varmuza and P. Filzmoser: Introduction to Multivariate Statistical Analysis in Chemometrics. CRC Press, Boca Raton, FL, 2009.

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