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Using JMP® Pro to Build Models Using Generalized Regression Variable Selection Techniques

gail_massari · 2020-09-24T19:39:58+00:00

See how to: * Build a response surface model for as many terms as needed * Examine Parameter Estimates VIF (Variable Inflation Factor) to identify highly correlated factors * Examine Prediction Profiler to identify collinearity * Publish prediction formulas to Formula Depot for subsequent model comparison * Use validation…

gail_massari

See how to:

Build a response surface model for as many terms as needed
Examine Parameter Estimates VIF (Variable Inflation Factor) to identify highly correlated factors
Examine Prediction Profiler to identify collinearity
Publish prediction formulas to Formula Depot for subsequent model comparison
Use validation to avoid model overfitting
Determine when and how to use advanced control options, including enforcing effect heredity, forcing terms, and early stopping
Use Variable Importance setting to organize Prediction Profiler by the most important factors
Build and compare models using Forward Selection (Stepwise), Ridge, Lasso, Double Lasso, Elastic Net and the adaptive Elastic Net regularization techniques to help identify key explanatory factors

Resources

Building Better Models with JMP Pro by Grayson, Gardner and Stephens
Files, including Production data not available in JMP Pro from JMP>Help>Sample Data, used in live Mastering JMP webcast, Using JMP Pro to Build Models Using Generalized Regression Variable Selection Techniques.