\HeaderA{parcoord}{Parallel Coordinates Plot}{parcoord}
\keyword{hplot}{parcoord}
\begin{Description}\relax
Parallel coordinates plot
\end{Description}
\begin{Usage}
\begin{verbatim}
parcoord(x, col = 1, lty = 1, ...)
\end{verbatim}
\end{Usage}
\begin{Arguments}
\begin{ldescription}
\item[\code{x}] a matrix or data frame who columns represent variables.

\item[\code{col}] A vector of colours, recycled as necessary for each observation.

\item[\code{lty}] A vector of line types, recycled as necessary for each observation.

\item[\code{...}] Further graphics parameters which are passed to \code{matplot}.

\end{ldescription}
\end{Arguments}
\begin{Section}{Side Effects}
a parallel coordinates plots is drawn.
\end{Section}
\begin{References}\relax
Wegman, E. J. (1990) Hyperdimensional data analysis using parallel
coordinates.
\emph{Journal of the American Statistical Association}
\bold{85}, 664--675.

Venables, W. N. and Ripley, B. D. (2002)
\emph{Modern Applied Statistics with S.} Fourth edition.  Springer.
\end{References}
\begin{Examples}
\begin{ExampleCode}
data(state)
parcoord(state.x77[, c(7, 4, 6, 2, 5, 3)])

data(iris3)
ir <- rbind(iris3[,,1], iris3[,,2], iris3[,,3])
parcoord(log(ir)[, c(3, 4, 2, 1)], col = 1 + (0:149)%/%50)
\end{ExampleCode}
\end{Examples}

