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📁 应用程序 偏最小二乘法回归分析 pls matlab
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<html><head><title>R: Partial Least Squares Regression (PLSR) and Principal Component
Regression (PCR)</title>
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<h1>Partial Least Squares Regression (PLSR) and Principal Component
Regression (PCR) <img class="toplogo" src="../../../doc/html/logo.jpg" alt="[R logo]"></h1>

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<h2>Documentation for package `pls' version 1.1-0</h2>

<h2>Help Pages</h2>


<table width="100%">
<tr><td width="25%"><a href="biplot.mvr.html">biplot.mvr</a></td>
<td>Biplots of PLSR and PCR Models.</td></tr>
<tr><td width="25%"><a href="coef.mvr.html">coef.mvr</a></td>
<td>Extract Information From a Fitted PLSR or PCR Model</td></tr>
<tr><td width="25%"><a href="coefplot.html">coefplot</a></td>
<td>Plot Regression Coefficients of PLSR and PCR models</td></tr>
<tr><td width="25%"><a href="coef.mvr.html">compnames</a></td>
<td>Extract Information From a Fitted PLSR or PCR Model</td></tr>
<tr><td width="25%"><a href="scoreplot.html">corrplot</a></td>
<td>Plots of Scores, Loadings and Correlation Loadings</td></tr>
<tr><td width="25%"><a href="crossval.html">crossval</a></td>
<td>Cross-validation of PLSR and PCR models</td></tr>
<tr><td width="25%"><a href="cvsegments.html">cvsegments</a></td>
<td>Generate segments for cross-validation</td></tr>
<tr><td width="25%"><a href="coef.mvr.html">explvar</a></td>
<td>Extract Information From a Fitted PLSR or PCR Model</td></tr>
<tr><td width="25%"><a href="kernelpls.fit.html">kernelpls.fit</a></td>
<td>Kernel PLS (Dayal and MacGregor)</td></tr>
<tr><td width="25%"><a href="scores.html">loading.weights</a></td>
<td>Extract Scores and Loadings from PLSR and PCR Models</td></tr>
<tr><td width="25%"><a href="scoreplot.html">loadingplot</a></td>
<td>Plots of Scores, Loadings and Correlation Loadings</td></tr>
<tr><td width="25%"><a href="msc.html">makepredictcall.msc</a></td>
<td>Multiplicative Scatter Correction</td></tr>
<tr><td width="25%"><a href="stdize.html">makepredictcall.stdized</a></td>
<td>Standardization of Data Matrices</td></tr>
<tr><td width="25%"><a href="coef.mvr.html">model.frame.mvr</a></td>
<td>Extract Information From a Fitted PLSR or PCR Model</td></tr>
<tr><td width="25%"><a href="coef.mvr.html">model.matrix.mvr</a></td>
<td>Extract Information From a Fitted PLSR or PCR Model</td></tr>
<tr><td width="25%"><a href="msc.html">msc</a></td>
<td>Multiplicative Scatter Correction</td></tr>
<tr><td width="25%"><a href="MSEP.html">MSEP</a></td>
<td>MSEP, RMSEP and R2 of PLSR and PCR models</td></tr>
<tr><td width="25%"><a href="mvr.html">mvr</a></td>
<td>Partial Least Squares and Principal Component Regression</td></tr>
<tr><td width="25%"><a href="mvrCv.html">mvrCv</a></td>
<td>Cross-validation</td></tr>
<tr><td width="25%"><a href="NIR.html">NIR</a></td>
<td>Multivariate Dataset of NIR Spectra</td></tr>
<tr><td width="25%"><a href="oscorespls.fit.html">oscorespls.fit</a></td>
<td>Orthogonal scores PLSR</td></tr>
<tr><td width="25%"><a href="mvr.html">pcr</a></td>
<td>Partial Least Squares and Principal Component Regression</td></tr>
<tr><td width="25%"><a href="scoreplot.html">plot.loadings</a></td>
<td>Plots of Scores, Loadings and Correlation Loadings</td></tr>
<tr><td width="25%"><a href="plot.mvr.html">plot.mvr</a></td>
<td>Plot Method for MVR objects</td></tr>
<tr><td width="25%"><a href="validationplot.html">plot.mvrVal</a></td>
<td>Validation Plots</td></tr>
<tr><td width="25%"><a href="scoreplot.html">plot.scores</a></td>
<td>Plots of Scores, Loadings and Correlation Loadings</td></tr>
<tr><td width="25%"><a href="mvr.html">plsr</a></td>
<td>Partial Least Squares and Principal Component Regression</td></tr>
<tr><td width="25%"><a href="msc.html">predict.msc</a></td>
<td>Multiplicative Scatter Correction</td></tr>
<tr><td width="25%"><a href="predict.mvr.html">predict.mvr</a></td>
<td>Predict Method for PLSR and PCR</td></tr>
<tr><td width="25%"><a href="stdize.html">predict.stdized</a></td>
<td>Standardization of Data Matrices</td></tr>
<tr><td width="25%"><a href="coef.mvr.html">prednames</a></td>
<td>Extract Information From a Fitted PLSR or PCR Model</td></tr>
<tr><td width="25%"><a href="predplot.html">predplot</a></td>
<td>Prediction Plots</td></tr>
<tr><td width="25%"><a href="predplot.html">predplotXy</a></td>
<td>Prediction Plots</td></tr>
<tr><td width="25%"><a href="summary.mvr.html">print.mvr</a></td>
<td>Summary and Print Methods for PLSR and PCR objects</td></tr>
<tr><td width="25%"><a href="summary.mvr.html">print.mvrVal</a></td>
<td>Summary and Print Methods for PLSR and PCR objects</td></tr>
<tr><td width="25%"><a href="MSEP.html">R2</a></td>
<td>MSEP, RMSEP and R2 of PLSR and PCR models</td></tr>
<tr><td width="25%"><a href="coef.mvr.html">respnames</a></td>
<td>Extract Information From a Fitted PLSR or PCR Model</td></tr>
<tr><td width="25%"><a href="MSEP.html">RMSEP</a></td>
<td>MSEP, RMSEP and R2 of PLSR and PCR models</td></tr>
<tr><td width="25%"><a href="scoreplot.html">scoreplot</a></td>
<td>Plots of Scores, Loadings and Correlation Loadings</td></tr>
<tr><td width="25%"><a href="scores.html">scores</a></td>
<td>Extract Scores and Loadings from PLSR and PCR Models</td></tr>
<tr><td width="25%"><a href="sensory.html">sensory</a></td>
<td>Multivariate Dataset of Sensory Data</td></tr>
<tr><td width="25%"><a href="simpls.fit.html">simpls.fit</a></td>
<td>Sijmen de Jong's SIMPLS</td></tr>
<tr><td width="25%"><a href="stdize.html">stdize</a></td>
<td>Standardization of Data Matrices</td></tr>
<tr><td width="25%"><a href="summary.mvr.html">summary.mvr</a></td>
<td>Summary and Print Methods for PLSR and PCR objects</td></tr>
<tr><td width="25%"><a href="svdpc.fit.html">svdpc.fit</a></td>
<td>Principal Component Regression</td></tr>
<tr><td width="25%"><a href="validationplot.html">validationplot</a></td>
<td>Validation Plots</td></tr>
<tr><td width="25%"><a href="scores.html">Yloadings</a></td>
<td>Extract Scores and Loadings from PLSR and PCR Models</td></tr>
<tr><td width="25%"><a href="scores.html">Yscores</a></td>
<td>Extract Scores and Loadings from PLSR and PCR Models</td></tr>
</table>
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