gamObject

A fitted GAM object returned by function <code>gam</code> and of class
<code>"gam"</code> inheriting from classes <code>"glm"</code> and <code>"lm"</code>. Method
functions <code>anova</code>, <code>logLik</code>, <code>influence</code>, <code>plot</code>,
<code>predict</code>, <code>print</code>, <code>residuals</code> and <code>summary</code> exist for
this class.<p></p><p>All compulsory elements of <code>"glm"</code> and <code>"lm"</code> objects are present,
but the fitting method for a GAM is different to a linear model or GLM, so
that the elements relating to the QR decomposition of the model matrix are
absent.
</p>

models

regression

smooth

GAMs, GAMMs and other generalized ridge regression with
multiple smoothing parameter estimation by GCV, REML or UBRE/AIC.
Includes a gam() function, a wide variety of smoothers, JAGS
support and distributions beyond the exponential family.

Simon Wood

mgcv

Mixed GAM Computation Vehicle with GCV/AIC/REML Smoothness
Estimation

gamObject function

This model object is different to that described in
Chambers and Hastie (1993) in order to allow smoothing parameter estimation etc. 

WARNINGS 

A fitted GAM object returned by function <code>gam</code> and of class
<code>"gam"</code> inheriting from classes <code>"glm"</code> and <code>"lm"</code>. Method
functions <code>anova</code>, <code>logLik</code>, <code>influence</code>, <code>plot</code>,
<code>predict</code>, <code>print</code>, <code>residuals</code> and <code>summary</code> exist for
this class.

All compulsory elements of <code>"glm"</code> and <code>"lm"</code> objects are present,
but the fitting method for a GAM is different to a linear model or GLM, so
that the elements relating to the QR decomposition of the model matrix are
absent.


gamObject: Fitted gam object

Description

Arguments

Value

WARNINGS

References

See Also