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<table width="100%" summary="page for parcoord {MASS}"><tr><td>parcoord {MASS}</td><td align="right">R Documentation</td></tr></table>
<h2>Parallel Coordinates Plot</h2>


<h3>Description</h3>

<p>
Parallel coordinates plot
</p>


<h3>Usage</h3>

<pre>
parcoord(x, col = 1, lty = 1, var.label = FALSE, ...)
</pre>


<h3>Arguments</h3>

<table summary="R argblock">
<tr valign="top"><td><code>x</code></td>
<td>
a matrix or data frame who columns represent variables.  Missing values
are allowed.
</td></tr>
<tr valign="top"><td><code>col</code></td>
<td>
A vector of colours, recycled as necessary for each observation.
</td></tr>
<tr valign="top"><td><code>lty</code></td>
<td>
A vector of line types, recycled as necessary for each observation.
</td></tr>
<tr valign="top"><td><code>var.label</code></td>
<td>
If <code>TRUE</code>, each variable's axis is labelled with maximum and
minimum values.
</td></tr>
<tr valign="top"><td><code>...</code></td>
<td>
Further graphics parameters which are passed to <code>matplot</code>.
</td></tr>
</table>

<h3>Side Effects</h3>

<p>
a parallel coordinates plots is drawn.
</p>


<h3>Author(s)</h3>

<p>
B. D. Ripley.  Enhancements based on ideas and code by Fabian Scheipl.
</p>


<h3>References</h3>

<p>
Wegman, E. J. (1990) Hyperdimensional data analysis using parallel
coordinates.
<EM>Journal of the American Statistical Association</EM>
<B>85</B>, 664&ndash;675.
</p>
<p>
Venables, W. N. and Ripley, B. D. (2002)
<EM>Modern Applied Statistics with S.</EM> Fourth edition.  Springer.
</p>


<h3>Examples</h3>

<pre>
parcoord(state.x77[, c(7, 4, 6, 2, 5, 3)])

ir &lt;- rbind(iris3[,,1], iris3[,,2], iris3[,,3])
parcoord(log(ir)[, c(3, 4, 2, 1)], col = 1 + (0:149)%/%50)
</pre>



<hr><div align="center">[Package <em>MASS</em> version 7.2-44 <a href="00Index.html">Index]</a></div>

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