gam2objective {mgcv} | R Documentation |

## Objective functions for GAM smoothing parameter estimation.

### Description

Estimation of GAM smoothing parameters is most stable if
optimization of the UBRE or GCV score is outer to the penalized iteratively
re-weighted least squares scheme used to estimate the model given smoothing
parameters. These functions evaluate the GCV/UBRE score of a GAM model, given
smoothing parameters, in a manner sutable for use by `optim`

or `nlm`

.
Not normally called directly, but rather service routines for `gam.outer`

.

### Usage

gam2objective(lsp,args)
gam2derivative(lsp,args)
gam3objective(lsp,args)

### Arguments

`lsp` |
The log smoothing parameters. |

`args` |
List of arguments required to call `gam.fit2` . |

### Details

`gam2objective`

and `gam2derivative`

are functions suitable
for calling by `optim`

, to evaluate the GCV/UBRE score and it's
derivatives w.r.t. log smoothing parameters.

`gam3objective`

is an equaivalent to `gam2objective`

, suitable for
optimization by `nlm`

- derivatives of the GCV/UBRE function are
calculated and returned as attributes.

The basic idea of optimizing smoothing parameters `outer' to the P-IRLS loop
was first proposed in O'Sullivan et al. (1986).

### Author(s)

Simon N. Wood simon.wood@r-project.org

### References

O 'Sullivan, Yandall & Raynor (1986) Automatic smoothing of regression
functions in generalized linear models. J. Amer. Statist. Assoc. 81:96-103.

http://www.stats.gla.ac.uk/~simon/

### See Also

`gam.fit2`

, `gam`

, `mgcv`

, `magic`

[Package

*mgcv* version 1.2-3

Index]