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
Suggests:
ChemoSpec,
chemometrics,
knitr,
tinytest,
roxut,
rmarkdown,
plot3D,
ade4,
plotrix,
latex2exp,
plotly,
xtable,
bookdown
Published:
2024年04月26日
Author:
Bryan A. Hanson
ORCID iD
[aut, cre],
David T. Harvey [aut]
Maintainer:
Bryan A. Hanson <hanson at depauw.edu>
NeedsCompilation:
no
Documentation:
Downloads:
Linking:
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https://CRAN.R-project.org/package=LearnPCA
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