# summary.rlm

From MASS v7.3-19
by Brian Ripley

##### 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. 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. stddev A scale estimate used for the standard errors. 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.

##### References

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

##### See Also

##### 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 7.3-19, License: GPL-2 | GPL-3*

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