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\name{parcoord}
\alias{parcoord}
\title{
Parallel Coordinates Plot
}
\description{
Parallel coordinates plot
}
\usage{
parcoord(x, col = 1, lty = 1, var.label = FALSE, \dots)
}
\arguments{
\item{x}{
a matrix or data frame who columns represent variables. Missing values
are allowed.
}
\item{col}{
A vector of colours, recycled as necessary for each observation.
}
\item{lty}{
A vector of line types, recycled as necessary for each observation.
}
\item{var.label}{
If \code{TRUE}, each variable's axis is labelled with maximum and
minimum values.
}
\item{\dots}{
Further graphics parameters which are passed to \code{matplot}.
}}
\section{Side Effects}{
a parallel coordinates plots is drawn.
}
\references{
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.
}
\author{
B. D. Ripley. Enhancements based on ideas and code by Fabian Scheipl.
}
\examples{
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)
}
\keyword{hplot}
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