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Modeling and Multivariate Methods - SAS

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Chapter 21 Fitting Partial Least Squares Models 517<br />

Model Fit Options<br />

Figure 21.12 Plot of X Loadings<br />

Loading Scatterplot Matrices<br />

the Y loadings.<br />

Shows a scatterplot matrix of the X loadings <strong>and</strong> a scatterplot matrix of<br />

Correlation Loading Plot Shows a scatterplot matrix of the X <strong>and</strong> Y loadings overlaid on the same plot.<br />

Check boxes enable you to control labeling.<br />

X-Y Score Plots Includes the following options:<br />

Fit Line Shows or hides a fitted line through the points on the X-Y Scores Plots.<br />

Show Confidence B<strong>and</strong> Shows or hides 95% confidence b<strong>and</strong>s for the fitted lines on the X-Y Scores<br />

Plots. Note that these should be used only for outlier detection.<br />

Score Scatterplot Matrices Shows a scatterplot matrix of the X scores <strong>and</strong> a scatterplot matrix of the Y<br />

scores. Each scatterplot displays a confidence ellipse. These may be used for outlier detection. For<br />

statistical details on the confidence ellipses, see “Confidence Ellipse for Scatter Scores Plots” on page 522.<br />

Distance Plots Shows a plot of the distance from each observation to the X model, the corresponding<br />

plot for the Y model, <strong>and</strong> a scatterplot of distances to both the X <strong>and</strong> Y models (Figure 21.13). In a good<br />

model, both X <strong>and</strong> Y distances are small, so the points are close to the origin (0,0). Use the plots to look<br />

for outliers relative to either X or Y. If a group of points clusters together, then they might have a<br />

common feature <strong>and</strong> could be analyzed separately.

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