Functions, Data Sets and Vignettes to Aid in Learning Principal Components Analysis (PCA)

Principal component analysis (PCA) is one of the most widely used data analysis techniques. This package provides a series of vignettes explaining PCA starting from basic concepts. The primary purpose is to serve as a self-study resource for anyone wishing to understand PCA better. A few convenience functions are provided as well.

See also

Useful links:

• https://bryanhanson.github.io/LearnPCA/

• Report bugs at https://github.com/bryanhanson/LearnPCA/issues

Author

Bryan A. Hanson and David T. Harvey. Maintainer: Bryan A. Hanson hanson@depauw.edu