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summary.glm {stats}R Documentation

Summarizing Generalized Linear Model Fits

Description

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

Usage

## 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"), ...)

Arguments

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.

Details

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.

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 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.

symbolic.cor

(only if correlation is true.) The value of the argument symbolic.cor.

See Also

glm, summary.

Examples

## --- Continuing the Example from  '?glm':%\code{\link{glm}}:

summary(glm.D93)
[Package stats version 2.0.0 ]