\HeaderA{summary.rlm}{Summary Method for Robust Linear Models}{summary.rlm}
\aliasA{print.summary.rlm}{summary.rlm}{print.summary.rlm}
\keyword{robust}{summary.rlm}
\begin{Description}\relax
\code{summary} method for objects of class \code{"rlm"}
\end{Description}
\begin{Usage}
\begin{verbatim}
## S3 method for class 'rlm':
summary(object, method = c("XtX", "XtWX"), correlation = TRUE, ...)
\end{verbatim}
\end{Usage}
\begin{Arguments}
\begin{ldescription}
\item[\code{object}] the fitted model.
This is assumed to be the result of some fit that produces
an object inheriting from the class \code{rlm}, in the sense that
the components returned by the \code{rlm} function will be available.

\item[\code{method}] Should the weighted (by the IWLS weights) or unweighted cross-products
matrix be used?

\item[\code{correlation}] logical. Should correlations be computed (and printed)?

\item[\code{...}] arguments passed to or from other methods.

\end{ldescription}
\end{Arguments}
\begin{Details}\relax
This function is a method for the generic function
\code{summary()} for class \code{"rlm"}.
It can be invoked by calling \code{summary(x)} for an
object \code{x} of the appropriate class, or directly by
calling \code{summary.rlm(x)} regardless of the
class of the object.
\end{Details}
\begin{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 \code{summary} function.

\begin{ldescription}
\item[\code{correlation}] The computed correlation coefficient matrix for the coefficients in the model.

\item[\code{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.

\item[\code{sigma}] The scale estimate.

\item[\code{df}] The number of degrees of freedom for the model and for residuals.

\item[\code{coefficients}] A matrix with three columns, containing the coefficients, their standard errors
and the corresponding t statistic.

\item[\code{terms}] The terms object used in fitting this model.

\end{ldescription}
\end{Value}
\begin{References}\relax
Venables, W. N. and Ripley, B. D. (2002)
\emph{Modern Applied Statistics with S.} Fourth edition.  Springer.
\end{References}
\begin{SeeAlso}\relax
\code{\LinkA{summary}{summary}}
\end{SeeAlso}
\begin{Examples}
\begin{ExampleCode}
summary(rlm(calls ~ year, data = phones, maxit = 50))
## Not run: 
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

## End(Not run)\end{ExampleCode}
\end{Examples}

