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.

Version: 0.3.4
Depends: rpart, class, nnet
Imports: markdown, shiny, stats, graphics
Suggests: ChemoSpec, chemometrics, knitr, tinytest, roxut, rmarkdown, plot3D, ade4, plotrix, latex2exp, plotly, xtable, bookdown
Published: 2024-04-26
DOI: 10.32614/CRAN.package.LearnPCA
Author: Bryan A. Hanson ORCID iD [aut, cre], David T. Harvey [aut]
Maintainer: Bryan A. Hanson <hanson at depauw.edu>
BugReports: https://github.com/bryanhanson/LearnPCA/issues
License: GPL-3
URL: https://bryanhanson.github.io/LearnPCA/
NeedsCompilation: no
Materials: NEWS
In views: ChemPhys
CRAN checks: LearnPCA results


Reference manual: LearnPCA.pdf
Vignettes: Vignette 01: A Guide to Learning PCA with LearnPCA (Start Here)
Vignette 02: A Conceptual Introduction to PCA
Vignette 03: Step-by-Step PCA
Vignette 04: Understanding Scores and Loadings
Vignette 05: Visualizing PCA in 3D
Vignette 06: The Math Behind PCA
Vignette 07: Functions for PCA
Vignette 08: Notes


Package source: LearnPCA_0.3.4.tar.gz
Windows binaries: r-devel: LearnPCA_0.3.4.zip, r-release: LearnPCA_0.3.4.zip, r-oldrel: LearnPCA_0.3.4.zip
macOS binaries: r-release (arm64): LearnPCA_0.3.4.tgz, r-oldrel (arm64): LearnPCA_0.3.4.tgz, r-release (x86_64): LearnPCA_0.3.4.tgz, r-oldrel (x86_64): LearnPCA_0.3.4.tgz
Old sources: LearnPCA archive


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