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<html><head><title>R: Prediction Plots</title>
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<table width="100%" summary="page for predplot {pls}"><tr><td>predplot {pls}</td><td align="right">R Documentation</td></tr></table>
<h2>Prediction Plots</h2>
<h3>Description</h3>
<p>
Functions to plot predicted values against measured values for a
fitted model.
</p>
<h3>Usage</h3>
<pre>
predplot(object, ...)
## Default S3 method:
predplot(object, ...)
## S3 method for class 'mvr':
predplot(object, ncomp = object$ncomp, which, newdata, nCols,
nRows, xlab = "measured", ylab = "predicted",
font.main = 1, cex.main = 1.1, ...)
predplotXy(x, y, line = FALSE, main = "Prediction plot",
xlab = "measured response", ylab = "predicted response", ...)
</pre>
<h3>Arguments</h3>
<table summary="R argblock">
<tr valign="top"><td><code>object</code></td>
<td>
a fitted model.</td></tr>
<tr valign="top"><td><code>ncomp</code></td>
<td>
integer vector. The model sizes (numbers of components)
to use for prediction.</td></tr>
<tr valign="top"><td><code>which</code></td>
<td>
character vector. Which types of predictions to plot.
Should be a subset of <code>c("train", "validation", "test")</code>. If not
specified, <code>plot.mvr</code> selects test set predictions if
<code>newdata</code> is supplied, otherwise cross-validated predictions if
the model has been cross-validated, otherwise fitted values from the
calibration data.</td></tr>
<tr valign="top"><td><code>newdata</code></td>
<td>
data frame. New data to predict.</td></tr>
<tr valign="top"><td><code>nCols, nRows</code></td>
<td>
integer. The number of coloumns and rows the
plots will be laid out in. If not specified, <code>plot.mvr</code> tries
to be intelligent.</td></tr>
<tr valign="top"><td><code>x</code></td>
<td>
numeric vector. The observed response values.</td></tr>
<tr valign="top"><td><code>y</code></td>
<td>
numeric vector. The predicted response values.</td></tr>
<tr valign="top"><td><code>line</code></td>
<td>
logical. Whether a target line should be shown.</td></tr>
<tr valign="top"><td><code>main</code></td>
<td>
character. Main title of plot.</td></tr>
<tr valign="top"><td><code>xlab,ylab</code></td>
<td>
titles for <i>x</i> and <i>y</i> axes. Typically
character strings, but can be expressions or lists. See
<code><a href="../../graphics/html/title.html">title</a></code> for details.</td></tr>
<tr valign="top"><td><code>font.main</code></td>
<td>
font to use for main title. See <code><a href="../../graphics/html/par.html">par</a></code>
for details.</td></tr>
<tr valign="top"><td><code>cex.main</code></td>
<td>
numeric. The magnification to be used for main titles
relative to the current size.</td></tr>
<tr valign="top"><td><code>...</code></td>
<td>
further arguments sent to underlying plot functions.</td></tr>
</table>
<h3>Details</h3>
<p>
<code>predplot</code> is a generic function for plotting predicted versus
measured response values, with default and <code>mvr</code> methods
currently implemented. The default method is very simple, and doesn't
handle multiple responses or new data.
</p>
<p>
The <code>mvr</code> method, <code>predplot.mvr</code> handles multiple responses,
model sizes and types of predictions by making one plot for each
combination. It can also be called through the plot method for
<code>mvr</code>, by specifying <code>plottype = "prediction"</code> (the
default).
</p>
<p>
<code>predplotXy</code> is an internal function and is not meant for
interactive use.
</p>
<h3>Value</h3>
<p>
The functions invisibly returns a matrix with the (last) plotted data.</p>
<h3>Author(s)</h3>
<p>
Ron Wehrens and Bj鴕n-Helge Mevik
</p>
<h3>See Also</h3>
<p>
<code><a href="mvr.html">mvr</a></code>, <code><a href="plot.mvr.html">plot.mvr</a></code>
</p>
<h3>Examples</h3>
<pre>
data(NIR)
mod <- plsr(y ~ X, ncomp = 10, data = NIR[NIR$train,], validation = "CV")
## Not run:
predplot(mod, ncomp = 1:6)
plot(mod, ncomp = 1:6) # Equivalent to the previous
## Both cross-validated and test set predictions:
predplot(mod, ncomp = 4:6, which = c("validation", "test"),
newdata = NIR[!NIR$train,])
## End(Not run)
data(sensory)
mod.sens <- plsr(Quality ~ Panel, ncomp = 4, data = sensory)
## Not run: plot(mod.sens, ncomp = 2:4) # Several responses gives several plots
</pre>
<hr><div align="center">[Package <em>pls</em> version 1.1-0 <a href="00Index.html">Index]</a></div>
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