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 | a logical flag. If TRUE, the correlation matrix for the coefficients is included in the summary. The default is FALSE.
symbolic.cor | a logical flag. In summary.lm, if correlation is TRUE, symbolic.cor is included in the summary, and its value is the same as this argument. The default is FALSE.
x | an object of class summary.lm resembling the output of the summary.lm function.
signif.stars | a logical flat. If TRUE (the default), when you print the coefficient, "significance stars" are 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.
- 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 as follows.

residuals | the residuals for the model. These are the weighted residuals if weights were given in the model.
coefficients | a matrix with one row for each coefficient in the fitted model. The first column, "Estimate", gives the estimate of the coefficent, and the others give the standard error ("Std. Error"), t value ("t value"), and p value ("Pr(>|t|)") of the estimate.
aliased | a 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 returned only 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 6.1.5-18
Package Index