The Partial Least Squares (PLS) platform fits linear models based on factors, namely, linear combinations of the explanatory variables (Xs). These factors are obtained in a way that attempts to maximize the covariance between the Xs and the response or responses (Ys). PLS exploits the correlations between the Xs and the Ys to reveal underlying latent structures.
JMP Pro provides additional functionality, allowing you to conduct PLS Discriminant Analysis (PLS-DA), include a variety of model effects, utilize several validation methods, impute missing data, and obtain bootstrap estimates of the distributions of various statistics.
Figure 5.1 A Portion of a Partial Least Squares Report
