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<html><head><title>R: Multivariate Dataset of NIR Spectra</title>
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<table width="100%" summary="page for NIR {pls}"><tr><td>NIR {pls}</td><td align="right">R Documentation</td></tr></table>
<h2>Multivariate Dataset of NIR Spectra</h2>
<h3>Description</h3>
<p>
A training set consisting of 21 NIR spectra of PET yarns, measured at
268 wavelengths, and 21 corresponding densities. A test set of 7
samples is also provided. Many thanks to Erik Swierenga.
</p>
<h3>Usage</h3>
<pre>data(NIR)</pre>
<h3>Format</h3>
<p>
A data frame with components
<dl>
<dt>X</dt><dd>Numeric matrix of NIR measurements</dd>
<dt>y</dt><dd>Numeric vector of densities</dd>
<dt>train</dt><dd>Logical vector with <code>TRUE</code> for the training
samples and <code>FALSE</code> for the test samples</dd>
</dl>
<h3>Source</h3>
<p>
Swierenga H., de Weijer A. P., van Wijk R. J., Buydens L. M. C. (1999)
Strategy for constructing robust multivariate calibration models
<EM>Chemometrics and Intelligent Laboratoryy Systems</EM>, <B>49</B>(1), 1–17.
</p>
<hr><div align="center">[Package <em>pls</em> version 1.1-0 <a href="00Index.html">Index]</a></div>
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