# summary.glm

0th

Percentile

##### Summarizing Generalized Linear Model Fits

These functions are all methods for class glm or summary.glm objects.

Keywords
models, regression
##### Usage
# S3 method for glm
summary(object, dispersion = NULL, correlation = FALSE,
symbolic.cor = FALSE, …)# S3 method for summary.glm
print(x, digits = max(3, getOption("digits") - 3),

##### Value

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 inferred/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 coefficients (including aliased ones).
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.

glm, summary.
library(stats) ## For examples see example(glm)