gam.outer {mgcv}R Documentation

Minimize GCV or UBRE score of a GAM using ‘outer’ iteration

Description

Estimation of GAM smoothing parameters is most stable if optimization of the smoothness selection score (GCV, GACV, UBRE/AIC, REML, ML etc) is outer to the penalized iteratively re-weighted least squares scheme used to estimate the model given smoothing parameters.

This routine optimizes a smoothness selection score in this way. Basically the score is evaluated for each trial set of smoothing parameters by estimating the GAM for those smoothing parameters. The score is minimized w.r.t. the parameters numerically, using newton (default), bfgs, optim or nlm. Exact (first and second) derivatives of the score can be used by fitting with gam.fit3. This improves efficiency and reliability relative to relying on finite difference derivatives.

Not normally called directly, but rather a service routine for gam.

Usage

gam.outer(lsp,fscale,family,control,method,optimizer,
          criterion,scale,gamma,G,start=NULL,...)

Arguments

lsp

The log smoothing parameters.

fscale

Typical scale of the GCV or UBRE/AIC score.

family

the model family.

control

control argument to pass to gam.fit if pure finite differencing is being used.

method

method argument to gam defining the smoothness criterion to use (but depending on whether or not scale known).

optimizer

The argument to gam defining the numerical optimization method to use.

criterion

Which smoothness selction criterion to use. One of "UBRE", "GCV", "GACV", "REML" or "P-REML".

scale

Supplied scale parameter. Positive indicates known.

gamma

The degree of freedom inflation factor for the GCV/UBRE/AIC score.

G

List produced by mgcv:::gam.setup, containing most of what's needed to actually fit a GAM.

start

starting parameter values.

...

other arguments, typically for passing on to gam.fit3 (ultimately).

Details

See Wood (2008) for full details on ‘outer iteration’.

Author(s)

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

References

Wood, S.N. (2011) Fast stable restricted maximum likelihood and marginal likelihood estimation of semiparametric generalized linear models. Journal of the Royal Statistical Society (B) 73(1):3-36

http://www.maths.bris.ac.uk/~sw15190/

See Also

gam.fit3, gam, magic


[Package mgcv version 1.8-31 Index]