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dglm.object |
Double generalized linear model object |

**DESCRIPTION**- Class of objects returned by fitting double generalized linear models.
**GENERATION**- 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. **METHODS**- 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`. **STRUCTURE**- 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. **SEE ALSO**- dglm

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