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 [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 resultsRetroSearch is an open source project built by @garambo | Open a GitHub Issue
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