The PLS Procedure

ODS Graphics

Statistical procedures use ODS Graphics to create graphs as part of their output. ODS Graphics is described in detail in ChapterĀ 24, Statistical Graphics Using ODS.

Before you create graphs, ODS Graphics must be enabled (for example, by specifying the ODS GRAPHICS ON statement). For more information about enabling and disabling ODS Graphics, see the section Enabling and Disabling ODS Graphics in ChapterĀ 24, Statistical Graphics Using ODS.

The overall appearance of graphs is controlled by ODS styles. Styles and other aspects of using ODS Graphics are discussed in the section A Primer on ODS Statistical Graphics in ChapterĀ 24, Statistical Graphics Using ODS.

When ODS Graphics is enabled, 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 ODS Graphics is enabled, but you can produce many other plots for the PROC PLS analysis.

ODS Graph Names

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 4.

Table 4: Graphs Produced by PROC PLS

ODS Graph Name Plot Description Option
CorrLoadPlot Correlation loading plot (default) PLOT=CORRLOAD(option)
CVPlot Cross validation and R-square analysis (default, as appropriate) CV=
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


Last updated: December 09, 2022