gam.fit

This is an internal function of package <code>mgcv</code>. It is a modification
  of the function <code>glm.fit</code>, designed to be called from <code>gam</code>. 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 <code>mgcv</code>. For further information on usage see code for <code>gam</code>.

models

regression

smooth

Routines for GAMs and other generalized ridge regression problems 
             with multiple smoothing parameter selection by GCV or UBRE.
             Includes an implementation (not a clone) of gam().

Simon Wood

mgcv

Multiple smoothing parameter estimation and GAMs by GCV

gam.fit function

The code does not check for rank defficiency of the
model matrix -
      it will likely just fail instead!

gam.fit: Generalized Additive Models fitting using penalized regression splines and GCV

Description

Arguments

WARNING

References

See Also