Package: jvcoords 1.0.3

jvcoords: Principal Component Analysis (PCA) and Whitening

Provides functions to standardize and whiten data, and to perform Principal Component Analysis (PCA). The main advantage of this package over alternatives like prcomp() is, that jvcoords makes it easy to convert (additional) data between the original and the transformed coordinates. The package also provides a class coords, which can represent affine coordinate transformations. This class forms the basis of the transformations provided by the package, but can also be used independently. The implementation has been optimized to be of comparable speed (and sometimes even faster) than existing alternatives.

Authors:Jochen Voss [aut, cre]

jvcoords_1.0.3.tar.gz
jvcoords_1.0.3.zip(r-4.5)jvcoords_1.0.3.zip(r-4.4)jvcoords_1.0.3.zip(r-4.3)
jvcoords_1.0.3.tgz(r-4.4-any)jvcoords_1.0.3.tgz(r-4.3-any)
jvcoords_1.0.3.tar.gz(r-4.5-noble)jvcoords_1.0.3.tar.gz(r-4.4-noble)
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jvcoords.pdf |jvcoords.html
jvcoords/json (API)
NEWS

# Install 'jvcoords' in R:
install.packages('jvcoords', repos = c('https://seehuhn.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://github.com/seehuhn/jvcoords/issues

On CRAN:

2.15 score 14 scripts 225 downloads 7 exports 0 dependencies

Last updated 3 years agofrom:5a1a3a2444. Checks:OK: 7. Indexed: yes.

TargetResultDate
Doc / VignettesOKNov 16 2024
R-4.5-winOKNov 16 2024
R-4.5-linuxOKNov 16 2024
R-4.4-winOKNov 16 2024
R-4.4-macOKNov 16 2024
R-4.3-winOKNov 16 2024
R-4.3-macOKNov 16 2024

Exports:appendTrfmcoordsfromCoordsPCAstandardizetoCoordswhiten

Dependencies: