ridgetorus: PCA on the Torus via Density Ridges
Implementation of a Principal Component Analysis (PCA) in the
torus via density ridge estimation. The main function, ridge_pca(), obtains
the relevant density ridge for bivariate sine von Mises and bivariate
wrapped Cauchy distribution models and provides the associated scores and
variance decomposition. Auxiliary functions for evaluating, fitting, and
sampling these models are also provided. The package provides replicability
to García-Portugués and Prieto-Tirado (2023)
<doi:10.1007/s11222-023-10273-9>.
Version: |
1.0.2 |
Depends: |
R (≥ 3.5.0), Rcpp |
Imports: |
rootSolve, sdetorus, sphunif, circular |
LinkingTo: |
Rcpp, RcppArmadillo |
Suggests: |
BAMBI, covr, DirStats, GGally, ggplot2, knitr, markdown, mvtnorm, numDeriv, rmarkdown, testthat, viridisLite |
Published: |
2023-08-27 |
DOI: |
10.32614/CRAN.package.ridgetorus |
Author: |
Eduardo García-Portugués
[aut, cre],
Arturo Prieto-Tirado
[aut] |
Maintainer: |
Eduardo García-Portugués <edgarcia at est-econ.uc3m.es> |
BugReports: |
https://github.com/egarpor/ridgetorus |
License: |
GPL-3 |
URL: |
https://github.com/egarpor/ridgetorus |
NeedsCompilation: |
yes |
Citation: |
ridgetorus citation info |
Materials: |
NEWS |
CRAN checks: |
ridgetorus results |
Documentation:
Downloads:
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