User guide

Partial least squares (PLS) is a multivariate statistical technique that aims to find shared information between two sets of variables. If you’re unfamiliar with PLS and are interested in a thorough (albeit quite technical) treatment, Abdi et al., 2013 is a good resource.

This user guide will go through the basic statistical concepts of the two types of PLS implemented in the current package (Behavioral PLS and Mean-centered PLS) and demonstrate how to interpret and use the results of a PLS analysis (PLS Results). If you still have questions after going through this guide then you can refer to the Reference API!

Table of Contents

• 1. Behavioral PLS
  • 1.1. What exactly do we mean by “behavioral PLS”?
  • 1.2. An exercise in calisthenics
  • 1.3. The cross-covariance matrix
  • 1.4. Singular value decomposition
  • 1.5. Latent variable significance testing
  • 1.6. Reliability of the singular vectors
• 2. Mean-centered PLS
  • 2.1. An oenological example
• 3. PLS Results