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,printWarn=FALSE)
    gam2derivative(lsp,args)
    gam3objective(lsp,args)

### Arguments

`lsp` | The log smoothing parameters.
`args` | List of arguments required to call `gam.fit2`.
`printWarn` | Should `gam.fit2` print some warnings? Used to suppress warnings that are only of interest for the final fitted model, until that model is reached.

### 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.maths.bath.ac.uk/~sw283/

### See Also

`gam.fit2`, `gam`, `mgcv`, `magic`

[Package mgcv version 1.3-17 Index]