riemannianStats: Riemannian Methods for Principal Component Analysis, Regression and Visualization

Provides tools for statistical analysis on Riemannian manifolds using local geometry derived from Uniform Manifold Approximation and Projection (UMAP), Isometric Mapping (Isomap), and Density-Based Spatial Clustering of Applications with Noise (DBSCAN). The package supports dimensionality reduction, visualization, Riemannian principal component analysis, and Riemannian linear regression for multivariate data analysis. Methods based on Uniform Manifold Approximation and Projection follow McInnes et al. (2018) <doi:10.21105/joss.00861>.

Version:	0.2.0
Depends:	R (≥ 4.1)
Imports:	rlang, ggplot2, ggrepel, grid, uwot, vegan, dbscan
Suggests:	scatterplot3d, plotly, testthat (≥ 3.0.0), knitr, rmarkdown
Published:	2026-07-23
DOI:	10.32614/CRAN.package.riemannianStats
Author:	Oldemar Rodríguez Rojas [aut, cre], Jennifer Lobo Vásquez [aut]
Maintainer:	Oldemar Rodríguez Rojas <oldemar.rodriguez at ucr.ac.cr>
License:	BSD_3_clause + file LICENSE
NeedsCompilation:	no
Language:	en-US
CRAN checks:	riemannianStats results

Documentation:

Reference manual:	riemannianStats.html , riemannianStats.pdf
Vignettes:	Step-by-Step Riemannian PCA with UMAP on Synthetic Data (source, R code) Classical and Riemannian Linear Regression with UMAP, ISOMAP, and DBSCAN (source, R code) Complete Riemannian PCA Workflow with riem.pca (source, R code) Step-by-Step Riemannian PCA with UMAP Similarities (source, R code)

Downloads:

Package source:	riemannianStats_0.2.0.tar.gz
Windows binaries:	r-devel: riemannianStats_0.2.0.zip, r-release: riemannianStats_0.2.0.zip, r-oldrel: riemannianStats_0.2.0.zip
macOS binaries:	r-release (arm64): riemannianStats_0.2.0.tgz, r-oldrel (arm64): riemannianStats_0.2.0.tgz, r-release (x86_64): riemannianStats_0.2.0.tgz, r-oldrel (x86_64): riemannianStats_0.2.0.tgz
Old sources:	riemannianStats archive

Linking:

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