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

Estimates the penalty coefficient from the generalized cross-validation criterion.

1 |

`y` |
The response vector. |

`x` |
A vector/matrix giving the values of the predictor
variable(s). If |

`knots` |
A vector givint the coordinates of the knots. |

`degree` |
The degree of the penalized smoothing spline. |

`plot` |
Logical. If |

`n.points` |
A numeric giving the number of CV computations needed to produce the plot. |

`...` |
Options to be passed to the |

For every linear smoother e.g. *y.hat =
S_λ y*, the cross-validation criterion consists in minimizing
the following quantity:

*GCV(λ) = (n ||y - y.hat||^2) / (n -
tr(S_λ))^2*

where *λ* is the penalty coefficient, *n* the
number of observations and *tr(S_λ)* is the
trace of the matrix *S_λ*.

A list with components 'penalty', 'gcv' and 'nlm.code' which give the
location of the minimum, the value of the cross-validation
criterion at that point and the code returned by the `link{nlm}`

function - useful to assess for convergence issues.

Mathieu Ribatet

Ruppert, D. Wand, M.P. and Carrol, R.J. (2003) *Semiparametric
Regression* Cambridge Series in Statistical and Probabilistic
Mathematics.

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