summary.gnm {gnm} | R Documentation |
summary
method for objects of class "gnm"
## 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$symbolic.cor, ...)
object |
an object of class "gnm" . |
x |
an object of class "summary.gnm" . |
dispersion |
the dispersion parameter for the fitting family. By
default it is obtained from object . |
correlation |
logical: if TRUE , the correlation matrix of
the estimated parameters is returned. |
digits |
the number of siginificant digits to use when printing. |
symbolic.cor |
logical: if TRUE , the correlations are
printed in a symbolic form rather than numbers (see symnum ). |
... |
further arguments passed to or from other methods. |
print.summary.gnm
prints the original call to gnm
; a
summary of the deviance residuals from the model fit; the coefficients
of the model; the residual deviance; the Akaike's Information
Criterion value; the number of main iterations performed, and if
requested, the correlation matrix.
Only the lower triangle of the correlation matrix is printed, to two
decimal places; to see the full matrix print summary(object,
correlation = TRUE)$correlation
directly.
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 . |
Heather Turner
## 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)