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 |
| 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 |
| 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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