This class of objects is returned by the
glm function
to represent a fitted generalized linear model.
Class
glm inherits from class
lm, since it is fit by iterative reweighted
least squares; the object returned has all the components of a weighted least squares object.
The class of
gam objects, on the other hand, inherit from class
glm.
Objects of this class have methods for the functions
print,
plot
,
summary,
anova,
predict,
fitted,
drop1,
add1, and
step,
amongst others.
The following components must be included in a legitimate
glm object.
The residuals, fitted values, coefficients and effects should be extracted
by the generic functions of the same name, rather than
by the
"$" operator.
The
family function returns the entire family object used in the fitting,
and
deviance can be used to extract the deviance of the fit.
linear.predictors, which multiply the
columns of the model
matrix.
The names of the coefficients are the names of the
single-degree-of-freedom effects (the columns of the
model matrix).
If the model is over-determined there will
be missing values in the coefficients corresponding to inestimable
coefficients.
fitted.values from the final weighted least squares fit.
linear.predictors
using the inverse link function.
lm object:
coefficients,
residuals,
fitted.values,
call,
terms and some
others involving the numerical fit. See
lm.object.