riemannianStats: Riemannian Statistics for Dimensionality Reduction and Visualization

Provides tools for applying statistical methods on Riemannian manifolds using local geometry derived from Uniform Manifold Approximation and Projection (UMAP). The package enables dimensionality reduction, visualization, and analysis of complex data through Riemannian versions of principal component analysis and related multivariate methods. Methods are based on McInnes et al. (2018) <doi:10.21105/joss.00861>.

Version:	0.1.1
Depends:	R (≥ 4.1)
Imports:	rlang, ggplot2, ggrepel, grid, uwot
Suggests:	scatterplot3d, plotly, testthat (≥ 3.0.0), knitr, rmarkdown
Published:	2026-07-17
DOI:	10.32614/CRAN.package.riemannianStats (may not be active yet)
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:	Data10D_250 Example (source, R code) Student example (source, R code)

Downloads:

Package source:	riemannianStats_0.1.1.tar.gz
Windows binaries:	r-devel: not available, r-release: riemannianStats_0.1.1.zip, r-oldrel: not available
macOS binaries:	r-release (arm64): riemannianStats_0.1.1.tgz, r-oldrel (arm64): riemannianStats_0.1.1.tgz, r-release (x86_64): riemannianStats_0.1.1.tgz, r-oldrel (x86_64): riemannianStats_0.1.1.tgz

Linking:

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