Summary Method for Robust Linear Models

Usage

summary.rlm(object, print.it=T, digits=4)

Arguments

object the fitted model. This is assumed to be the result of some fit that produces an object inheriting from the class rlm, in the sense that the components returned by the rlm function will be available.
print.it optional argument. If false, the standard printing will not take place, and instead a structure will be returned with components containing the important computed for summarizing, as below.
digits the number of digits to be used in printing summaries, in the sense of the argument to print of the same name.

Description

summary method for objects of class "rlm"

Details

This function is a method for the generic function summary() for class rlm. It can be invoked by calling summary(x) for an object x of the appropriate class, or directly by calling summary.rlm(x) regardless of the class of the object.

Value

If printing takes place, only a null value is returned. Otherwise, a list is returned with the following components. Printing always takes place if this function is invoked automatically as a method for the summary function.

correlation The computed correlation coefficient matrix for the coefficients in the model.
cov.unscaled The unscaled covariance matrix; i.e, a matrix such that multiplying it by an estimate of the error variance produces an estimated covariance matrix for the coefficients.
sigma The scale estimate.
df The number of degrees of freedom for the model and for residuals.
coefficients A matrix with three columns, containing the coefficients, their standard errors and the corresponding t statistic.
terms The terms object used in fitting this model.

See Also

summary

Examples

> data(phones)
> summary(rlm(calls ~ year, data=phones, maxit=50))

Call:
rlm(formula = calls ~ year, data = phones, maxit = 50)

Residuals:
   Min     1Q Median     3Q    Max 
-18.31  -5.95  -1.68  26.46 173.77 

Coefficients:
            Value    Std. Error t value
(Intercept) -102.622   26.553   -3.86  
year           2.041    0.429    4.76  

Residual standard error: 9.03 on 22 degrees of freedom

Correlation of Coefficients:
[1] -0.994

Residuals:
    Min     1Q Median    3Q   Max 
 -18.38 -5.976 -1.687 26.46 173.7

Coefficients:
                Value Std. Error   t value 
(Intercept) -102.8123   26.6804    -3.8535
       year    2.0449    0.4311     4.7435

Residual standard error: 9.078 on 22 degrees of freedom

Correlation of Coefficients:
     (Intercept) 
year -0.9937

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