||Double generalized linear model object
- Class of objects returned by fitting double generalized
- This class of objects is returned by the dglm
function to represent a fitted double generalized linear
model. Class dglm inherits from class glm,
since it consists of two coupled generalized linear
models, one for the mean and one for the dispersion. Like
glm, it also inherits from lm. The
object returned has all the components of a glm
object. The returned component object$dispersion.fit
is also a glm object in its own right,
representing the result of modelling the dispersion.
- Objects of this class have methods for the functions print,
plot, summary, anova, predict,
fitted, drop1, add1, and step,
amongst others. Specific methods (not shared with glm)
exist for summary and anova.
- A dglm object consists of a glm object
with the following additional components:
||the dispersion submodel: a glm
object representing the fitted model for the
dispersions. The responses for this model are the
deviance components from the original generalized
linear model. The prior weights are 1 and the
dispersion or scale of this model is 2.
||this component now represents the number of
outer iterations used to fit the coupled
mean-dispersion models. At each outer iteration,
one IRLS is done for each of the mean and
||fitting method used: "ml" if
maximum likelihood was used or "reml"
if adjusted profile likelihood was used.
||minus twice the log-likelihood or adjusted
profile likelihood of the fitted model.
- SEE ALSO
Copyright © 1996-2016. Last modified:
10 February 2004