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) .


Reference manual

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install.packages("ridgetorus")

1.1.0 by Eduardo García-Portugués, 3 months ago


https://github.com/egarpor/ridgetorus


Report a bug at https://github.com/egarpor/ridgetorus/issues


Browse source code at https://github.com/cran/ridgetorus


Authors: Eduardo García-Portugués [aut, cre] (ORCID: , Arturo Prieto-Tirado [aut] (ORCID:


Documentation:   PDF Manual  


GPL-3 license


Imports rootSolve, sdetorus, sphunif, circular

Depends on Rcpp

Suggests BAMBI, covr, DirStats, GGally, ggplot2, knitr, markdown, mvtnorm, numDeriv, rmarkdown, testthat, viridisLite

Linking to Rcpp, RcppArmadillo


See at CRAN