| summary.glm {stats} | R Documentation |
These functions are all methods for class glm or
summary.glm objects.
## S3 method for class 'glm':
summary(object, dispersion = NULL, correlation = FALSE,
symbolic.cor = FALSE, ...)
## S3 method for class 'summary.glm':
print(x, digits = max(3, getOption("digits") - 3),
symbolic.cor = x$symbolic.cor,
signif.stars = getOption("show.signif.stars"), ...)
object |
an object of class "glm", usually, a result of a
call to glm. |
x |
an object of class "summary.glm", usually, a result of a
call to summary.glm. |
dispersion |
the dispersion parameter for the fitting family.
By default it is obtained from object. |
correlation |
logical; if TRUE, the correlation matrix of
the estimated parameters is returned and printed. |
digits |
the number of significant digits to use when printing. |
symbolic.cor |
logical. If TRUE, print the correlations in
a symbolic form (see symnum) rather than as numbers. |
signif.stars |
logical. If TRUE, “significance stars”
are printed for each coefficient. |
... |
further arguments passed to or from other methods. |
print.summary.glm tries to be smart about formatting the
coefficients, standard errors, etc. and additionally gives
“significance stars” if signif.stars is TRUE.
Aliased coefficients are omitted in the returned object but (as from R
1.8.0) restored by the print method.
Correlations are printed to two decimal places (or symbolically): to
see the actual correlations print summary(object)$correlation
directly.
The dispersion is taken as 1 in the binomial and
Poisson families, and otherwise estimated by the residual
Chisquared statistic divided by the residual degrees of freedom.
summary.glm returns an object of class "summary.glm", a
list with components
call |
the component from object. |
family |
the component from object. |
deviance |
the component from object. |
contrasts |
the component from object. |
df.residual |
the component from object. |
null.deviance |
the component from object. |
df.null |
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 is 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. |
symbolic.cor |
(only if correlation is true.) The value
of the argument symbolic.cor. |
## --- Continuing the Example from '?glm': summary(glm.D93)