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dglm.object   Double generalized linear model object
Class of objects returned by fitting double generalized linear models.
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:
dispersion.fit   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.
iter   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 dispersion submodels.
method   fitting method used: "ml" if maximum likelihood was used or "reml" if adjusted profile likelihood was used.
m2loglik   minus twice the log-likelihood or adjusted profile likelihood of the fitted model.


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Gordon Smyth. Copyright © 1996-2016. Last modified: 10 February 2004