lignin sulfonate (ls), which is pulp industry pollution
humic acid (ha), which is a natural forest product
1.
Select Help > Sample Data Library and open Baltic.jmp.
Note: The data in the Baltic.jmp data table are reported in Umetrics (1995). The original source is Lindberg, Persson, and Wold (1983).
2.
Select Analyze > Multivariate Methods > Partial Least Squares.
3.
Assign ls, ha, and dt to the Y, Response role.
4.
Assign Intensities, which contains the 27 intensity variables v1 through v27, to the X, Factor role.
5.
6.
Select Leave-One-Out as the Validation Method.
7.
A portion of the report appears in Figure 5.2. Since the van der Voet test is a randomization test, your Prob > van der Voet T2 values can differ slightly from those in Figure 5.2.
Figure 5.2 Partial Least Squares Report
The van der Voet T2 statistic tests to determine whether a model with a different number of factors differs significantly from the model with the minimum PRESS value. A common practice is to extract the smallest number of factors for which the van der Voet significance level exceeds 0.10 (SAS Institute Inc 2017d; Tobias 1995). If you were to apply this thinking here, you would fit a new model by entering 6 as the Number of Factors in the Model Launch panel.
Figure 5.3 Seven Extracted Factors
8.
Select Diagnostics Plots from the NIPALS Fit with 7 Factors red triangle menu.
Figure 5.4 Diagnostics Plots
9.
Select VIP vs Coefficients Plot from the NIPALS Fit with 7 Factors red triangle menu.
Figure 5.5 VIP vs Coefficients Plot

Help created on 7/12/2018