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:
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)
jvcoords_1.0.3.tgz(r-4.4-emscripten)jvcoords_1.0.3.tgz(r-4.3-emscripten)
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')) |
Bug tracker:https://github.com/seehuhn/jvcoords/issues
Last updated 3 years agofrom:5a1a3a2444. Checks:OK: 7. Indexed: yes.
Target | Result | Date |
---|---|---|
Doc / Vignettes | OK | Nov 16 2024 |
R-4.5-win | OK | Nov 16 2024 |
R-4.5-linux | OK | Nov 16 2024 |
R-4.4-win | OK | Nov 16 2024 |
R-4.4-mac | OK | Nov 16 2024 |
R-4.3-win | OK | Nov 16 2024 |
R-4.3-mac | OK | Nov 16 2024 |
Exports:appendTrfmcoordsfromCoordsPCAstandardizetoCoordswhiten
Dependencies:
Readme and manuals
Help Manual
Help page | Topics |
---|---|
Package overview | jvcoords-package |
An S3 class to represent affine coordinate transforms | appendTrfm coords fromCoords toCoords |
Perform Principal Component Analysis (PCA) | PCA |
Standardize data | standardize |
Whiten data | whiten |