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Partial Least Squares Using JMP Pro - Slides and Case Study Data

Slides and case study data used in Peter Bartell's  live Advanced Mastering JMP webinar, Partial Least Squares: When Ordinary Least Squares Regression Just Won't Work. 

 

PLS is useful: to construct predictive models when you have many highly collinear (correlated) factors or more x variables than observations of the responses -and- when you need to predict responses and you’d like to find influential predictor variables –or- reduce the number of predictor variables for subsequent study.

 

View the videos made from his webinar.

 

Other resources on this topic include:

• SAS Press book Discovering Partial Least Squares with JMP by Cox and Gaudard and the accompanying example code and data.
• Micro Array Quality Control Study for classification of individuals based on gene expression characterization
• JMP PLS online documentation

ModelingRe: Partial Least Squares Using JMP Pro - Slides and Case Study Data

Thanks Gail for making this available.

Thanks Peter for case studies to understand PLS using JMP.