summary.dglm: Summarize Double Generalized Linear Model Fit

In dglm: Double Generalized Linear Models

Summarize Double Generalized Linear Model Fit

Description

Summarize objects of class "dglm".

Usage

## S3 method for class 'dglm'
summary(object, dispersion=NULL, correlation = FALSE, ...)

Arguments

object	an object of class "dglm".
dispersion	the dispersion parameter for the fitting family. By default it is obtained from object.
correlation	logical; if TRUE, the correlation matrix of the estimated parameters is returned and printed.
...	further arguments to be passed to summary.glm

Details

For more details, see summary.glm.

If more than one of etastart, start and mustart is specified, the first in the list will be used.

Value

An object of class "summary.dglm", which is a list with the following components:

call	the component from object
terms	the component from object
family	the component from object
deviance	the component from object
aic	NULL here
constrasts	(where relevant) the contrasts used. NOT WORKING??
df.residual	the component from object
null.deviance	the component from object
df.null	the residual degrees of freedom for the null model.
iter	the component from object
deviance.resid	the deviance residuals: see residuals.glm
coefficients	the matrix of coefficients, standard errors, z-values and p-values. Aliased coefficients are omitted.
aliased	named logical vector showing if the original coefficients are aliased.
dispersion	either the supplied argument or the estimated dispersion if the latter in NULL
df	a 3-vector of the rank of the model and the number of residual degrees of freedom, plus number of non-aliased coefficients.
cov.unscaled	the unscaled (dispersion = 1) estimated covariance matrix of the estimated coefficients.
cov.scaled	ditto, scaled by dispersion
correlation	(only if correlation is true.) The estimated correlations of the estimated coefficients.
dispersion.summary	the summary of the fitted dispersion model
outer.iter	the number of outer iteration of the alternating iterations
m2loglik	minus twice the log-likelihood of the fitted model

Note

The anova method is questionable when applied to an dglm object created with method="reml" (stick to method="ml").

Author(s)

Gordon Smyth, ported to R by Peter Dunn ([e-mail])

References

Smyth, G. K. (1989). Generalized linear models with varying dispersion. J. R. Statist. Soc. B, 51, 47–60. \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1111/j.2517-6161.1989.tb01747.x")}

Smyth, G. K., and Verbyla, A. P. (1999). Adjusted likelihood methods for modelling dispersion in generalized linear models. Environmetrics, 10, 696-709. \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1002/(SICI)1099-095X(199911/12)10:6<695::AID-ENV385>3.0.CO;2-M")} https://gksmyth.github.io/pubs/Ties98-Preprint.pdf

Smyth, G. K., and Verbyla, A. P. (1999). Double generalized linear models: approximate REML and diagnostics. In Statistical Modelling: Proceedings of the 14th International Workshop on Statistical Modelling, Graz, Austria, July 19-23, 1999, H. Friedl, A. Berghold, G. Kauermann (eds.), Technical University, Graz, Austria, pages 66-80. https://gksmyth.github.io/pubs/iwsm99-Preprint.pdf

See Also

dglm, dglm-class, summary.glm

dglm documentation built on Nov. 25, 2023, 9:07 a.m.