PCA modeling

For the modeling process, we will use the following steps:

1. Extract the components and determine the number to retain
2. Rotate the retained components
3. Interpret the rotated solution
4. Create scores from the non-rotated components
5. Use the scores as input variables for regression analysis with MARS and evaluate the performance on the test data

There are many different ways and packages used to conduct PCA in R, including what seems to be the most commonly used prcomp() and princomp() functions in base R. However, for my money, it seems that the psych package is the most flexible with the best options.

Component extraction

To extract the components with the psych package, you will use the principal() function. The syntax...