# summary.rlm

0th

Percentile

##### Summary Method for Robust Linear Models

summary method for objects of class "rlm"

Keywords
robust
##### Usage
## S3 method for class 'rlm':
summary(object, method = c("XtX", "XtWX"), correlation = FALSE, ...)
##### 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.
method
Should the weighted (by the IWLS weights) or unweighted cross-products matrix be used?
correlation
logical. Should correlations be computed (and printed)?
...
arguments passed to or from other methods.
##### 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.
• correlationThe computed correlation coefficient matrix for the coefficients in the model.
• cov.unscaledThe 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.
• sigmaThe scale estimate.
• stddevA scale estimate used for the standard errors.
• dfThe number of degrees of freedom for the model and for residuals.
• coefficientsA matrix with three columns, containing the coefficients, their standard errors and the corresponding t statistic.
• termsThe terms object used in fitting this model.

##### References

Venables, W. N. and Ripley, B. D. (2002) Modern Applied Statistics with S. Fourth edition. Springer.

summary

##### Aliases
• summary.rlm
• print.summary.rlm
##### Examples
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
Documentation reproduced from package MASS, version 7.3-23, License: GPL-2 | GPL-3

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