mgcv.control

conv.tol

successive step halvings are employed if the Newton method and then the steepest descent backup
fail to improve the UBRE/GCV score. This is how many to use before giving up.

max.half

If this is non-null it indicates that cautious optimization should be used, which 
opts for the local minimum closest to the target model edf if there are multiple local minima in the 
GCV/UBRE score.

target.edf

Lower bound on the model edf. Useful for avoiding numerical problems at high smoothing parameter
values. Negative for none.

min.edf

This is an internal function of package <code>mgcv</code> which allows control of the numerical 
options for fitting a generalized ridge regression problem using routine <code>mgcv</code>.

models

regression

smooth

Routines for GAMs and other generalized ridge regression  
             with multiple smoothing parameter selection by GCV or UBRE.
             Also GAMMs by REML or PQL. Includes a gam() function.

mgcv.control: Setting mgcv defaults

Description

Usage

Arguments

References

See Also