LearnPCA
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.
- Version0.3.4
- R versionunknown
- LicenseGPL-3
- Needs compilation?No
- Last release04/26/2024
Documentation
- VignetteVignette 01: A Guide to Learning PCA with LearnPCA (Start Here)
- VignetteVignette 02: A Conceptual Introduction to PCA
- VignetteVignette 03: Step-by-Step PCA
- VignetteVignette 04: Understanding Scores and Loadings
- VignetteVignette 05: Visualizing PCA in 3D
- VignetteVignette 06: The Math Behind PCA
- VignetteVignette 07: Functions for PCA
- VignetteVignette 08: Notes
- MaterialNEWS
- In ViewsChemPhys
Team
Bryan A. Hanson
David T. Harvey
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- Depends3 packages
- Imports4 packages
- Suggests13 packages