summary.lm
Summary Method for Linear Models

Description

Summarize a fitted linear model.

Usage

## S3 method for class 'lm':
summary(object, correlation = FALSE, symbolic.cor = FALSE, ...)
## S3 method for class 'mlm':
summary(object, correlation = FALSE, symbolic.cor = FALSE, ...)
## S3 method for class 'summary.lm':
print(x, digits = max(3, getOption("digits") - 3), symbolic.cor = x$symbolic.cor, signif.stars = getOption("show.signif.stars", default = TRUE), ...)

Arguments

object A fitted linear model inheriting from class lm or mlm, typically the output of the lm function when the response is a vector or a matrix, respectively.
correlation Logical flag. If TRUE, the correlation matrix for the coefficients is included in the summary.
symbolic.cor Logical flag. In summary.lm, if correlation is TRUE, symbolic.cor is included in the summary, and its value is the same to this argument.
x An object of class summary.lm, resembling the output of summary.lm function.
signif.stars logical flat. If TRUE, when print coefficient, "significance stars" will be printed.
digits an integer used in print, to indicate the number of significant digits to use when printing.
... extra arguments passed to or from other methods. The summary methods here ignore these arguments and the print methods pass them onto lower level printing routines.

Details

summary.lm produces a summary object of class summary.lm and print.summary.lm prints such an object. summary.mlm produces a list of class listof containing one summary.lm object for each column in the response matrix.
Value
summary.lm returns a list of class summary.lm whose components call and terms are copied from its object argument and whose other components are:
residuals the residuals for the model. These are the weighted residuals if weights were given in the model.
aliased logical vector to show if the original coefficients are aliased.
sigma the residual standard error estimate.
df a numeric vector of length three giving the rank of the model matrix, the residual degrees of freedom, and the number of coefficients for the model.
fstatistic a numeric vector of length three giving the F-test for the regression. The first element in the vector is the statistic, and the last two elements are the degrees of freedom.
r.squared the multiple R-squared statistic for the model.
adj.r.squared the adjusted multiple R-squared statistic for the model.
cov.unscaled the unscaled covariance matrix. Multiplying cov.unscaled by an estimate of the error variance produces an estimated covariance matrix for the coefficients.
correlation the computed correlation matrix for the coefficients in the model. This is only returned if correlation=TRUE was set.
symbolic.cor this item appears only when correlation is true. Its value is the value of the argument symbolic.cor.
See Also
lm, lm.object, summary, anova.
Examples
fit <- lm(ozone ~ radiation + temperature + wind, data=Sdatasets::air)
summary(fit)
Package stats version 4.0.0-28
Package Index