gam.fit {mgcv} | R Documentation |
This is an internal function of package mgcv
. It is a modification
of the function glm.fit
, designed to be called from gam
. The major
modification is that rather than solving a weighted least squares problem at each IRLS step,
a weighted, penalized least squares problem
is solved at each IRLS step with smoothing parameters associated with each penalty chosen by GCV or UBRE,
using routine mgcv
. For further information on usage see code for gam
.
The code does not check for rank defficiency of the model matrix - it will likely just fail instead!
Simon N. Wood simon@stats.gla.ac.uk
Gu and Wahba (1991) Minimizing GCV/GML scores with multiple smoothing parameters via the Newton method. SIAM J. Sci. Statist. Comput. 12:383-398
Wood (2000) Modelling and Smoothing Parameter Estimation with Multiple Quadratic Penalties. JRSSB 62(2):413-428
http://www.stats.gla.ac.uk/~simon/