The PLS Procedure |
ODS Graphics |
This section describes the use of ODS for creating statistical graphs with the PLS procedure. To request these graphs you must specify the ODS GRAPHICS statement. For more information about the ODS GRAPHICS statement, see Chapter 21, Statistical Graphics Using ODS.
When the ODS GRAPHICS are in effect, by default the PLS procedure produces a plot of the variation accounted for by each extracted factor, as well as a correlation loading plot for the first two extracted factors (if the final model has at least two factors). The plot of the variation accounted for can take several forms:
If the PLS analysis does not include cross validation, then the plot shows the total R square for both model effects and the dependent variables against the number of factors.
If you specify the CV= option to select the number of factors in the final model by cross validation, then the plot shows the R-square analysis discussed previously as well as the root mean PRESS from the cross validation analysis, with the selected number of factors identified by a vertical line.
The correlation loading plot for the first two factors summarizes many aspects of the two most significant dimensions of the model. It consists of overlaid scatter plots of the scores of the first two factors, the loadings of the model effects, and the loadings of the dependent variables. The loadings are scaled so that the amount of variation in the variables that is explained by the model is proportional to the distance from the origin; circles indicating various levels of explained variation are also overlaid on the correlation loading plot. Also, the correlation between the model approximations for any two variables is proportional to the length of the projection of the point corresponding to one variable on a line through the origin passing through the point corresponding to the other variable; the sign of the correlation corresponds to which side of the origin the projected point falls on.
The R square and the first two correlation loadings are plotted by default when the ODS GRAPHICS are in effect, but you can produce many other plots for the PROC PLS analysis.
PROC PLS assigns a name to each graph it creates using ODS. You can use these names to reference the graphs when using ODS. The names are listed in Table 67.3.
To request these graphs you must specify the ODS GRAPHICS statement. For more information about the ODS GRAPHICS statement, see Chapter 21, Statistical Graphics Using ODS.
ODS Graph Name |
Plot Description |
Option |
---|---|---|
CorrLoadPlot |
Correlation loading plot (default) |
PLOT=CORRLOAD(option) |
CVPlot |
Cross validation and R-square analysis (default, as appropriate) |
|
DModXPlot |
Distance of each observation to the X model |
PLOT=DMODX |
DModXYPlot |
Distance of each observation to the X and Y models |
PLOT=DMODXY |
DModYPlot |
Distance of each observation to the Y model |
PLOT=DMODY |
DiagnosticsPanel |
Panel of diagnostic plots for the fit |
PLOT=DIAGNOSTICS |
AbsResidualByPredicted |
Absolute residual by predicted values |
PLOT=DIAGNOSTICS(UNPACK) |
ObservedByPredicted |
Observed by predicted |
PLOT=DIAGNOSTICS(UNPACK) |
QQPlot |
Residual Q-Q plot |
PLOT=DIAGNOSTICS(UNPACK) |
ResidualByPredicted |
Residual by predicted values |
PLOT=DIAGNOSTICS(UNPACK) |
ResidualHistogram |
Residual histogram |
PLOT=DIAGNOSTICS(UNPACK) |
RFPlot |
RF plot |
PLOT=DIAGNOSTICS(UNPACK) |
ParmProfiles |
Profiles of regression coefficients |
PLOT=PARMPROFILES |
R2Plot |
R-square analysis (default, as appropriate) |
|
ResidualPlots |
Residuals for each dependent variable |
PLOT=RESIDUALS |
VariableImportancePlot |
Profile of variable importance factors |
PLOT=VIP |
XLoadingPlot |
Scatter plot matrix of X-loadings against each other |
PLOT=XLOADINGPLOT |
XLoadingProfiles |
Profiles of the X-loadings |
PLOT=XLOADINGPROFILES |
XScorePlot |
Scatter plot matrix of X-scores against each other |
PLOT=XSCORES |
XWeightPlot |
Scatter plot matrix of X-weights against each other |
PLOT=XWEIGHTPLOT |
XWeightProfiles |
Profiles of the X-weights |
PLOT=XWEIGHTPROFILES |
XYScorePlot |
Scatter plot matrix of X-scores against Y-scores |
PLOT=XYSCORES |
YScorePlot |
Scatter plot matrix of Y-scores against each other |
PLOT=YSCORES |
YWeightPlot |
Scatter plot matrix of Y-weights against each other |
PLOT=YWEIGHTPLOT |
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