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
.