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ridgetorus (version 1.0.3)

PCA on the Torus via Density Ridges

Description

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) .

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Install

install.packages('ridgetorus')

Monthly Downloads

202

Version

1.0.3

License

GPL-3

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Repository

https://github.com/egarpor/ridgetorus

Maintainer

Eduardo Portugues

Last Published

July 27th, 2025

Functions in ridgetorus (1.0.3)

Illustration of toroidal PCA via density ridges

Toroidal distances

Toroidal pairs plot

Scores and scales for Fourier-fitted ridge curves

Santa Barbara currents

ridgetorus-package

ridgetorus: PCA on the Torus via Density Ridges

ridge_fourier_fit

Fourier expansion of a given curve

Japanese earthquakes dataset

Tests of homogeneity and independence in bivariate sine von Mises and wrapped Cauchy distributions

Density evaluation, sampling, and parameter estimation of the bivariate wrapped Cauchy distribution

Density evaluation, sampling, and parameter estimation of the bivariate wrapped normal distribution

Connected component of the toroidal density ridge of a bivariate sine von Mises, bivariate wrapped Cauchy, and bivariate wrapped normal

Fourier-fitted ridge curve and related utilities

Fréchet statistics on the torus

Density evaluation, sampling, and parameter estimation of the bivariate sine von Mises distribution

Toroidal PCA via density ridges

Texas wind dataset