summary.gnm {gnm}R Documentation

Summarize Generalized Nonlinear Model Fits

Description

summary method for objects of class "gnm"

Usage

## S3 method for class 'gnm':
summary(object, dispersion = NULL, correlation = FALSE,
                      symbolic.cor = FALSE, ...)

## S3 method for class 'summary.gnm':
print(x, digits = max(3, getOption("digits") - 3),
                            symbolic.cor = x$symbolic.cor, ...)

Arguments

object an object of class "gnm".
x an object of class "summary.gnm".
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.
digits the number of siginificant digits to use when printing.
symbolic.cor logical: if TRUE, the correlations are printed in a symbolic form rather than numbers (see symnum).
... further arguments passed to or from other methods.

Details

print.summary.gnm prints the original call to gnm; a summary of the deviance residuals from the model fit; the coefficients of the model; the residual deviance; the Akaike's Information Criterion value; the number of main iterations performed, and if requested, the correlation matrix.

Only the lower triangle of the correlation matrix is printed, to two decimal places; to see the full matrix print summary(object, correlation = TRUE)$correlation directly.

Value

summary.gnm returns an object of class "summary.gnm", which is a list with components

call the "call" component from object.
terms the "terms" component from object.
family the "family" component from object.
deviance the "deviance" component from object.
aic the "aic" component from object.
df.residual the "df.residual" component from object.
iter the "iter" component from object.
deviance.resid the deviance residuals, see residuals.glm.
coefficients the "coefficients" component from object.
dispersion either the supplied argument or the estimated dispersion if the latter is NULL.
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.
symbolic.cor (only if correlation is true) the value of the argument symbolic.cor.

Author(s)

Heather Turner

See Also

gnm, summary

Examples

##  Following on from example(gnm)
data(cautres)
set.seed(1)

##  Fit model as before
doubleUnidiff <- gnm(Freq ~ election:vote + election:class:religion +
                     Mult(Exp(election), religion:vote) +
                     Mult(Exp(election), class:vote), family = poisson,
                     data = cautres)

## Summarize results
summary(doubleUnidiff)
[Package gnm version 0.6-1 Index]