Riemannian Methods for Principal Component Analysis, Regression and Visualization R package riemannianStats version 0.2.0 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>. Software Depends: R (>= 4.1) Imports: rlang, ggplot2, ggrepel, grid, uwot, vegan, dbscan Suggests: scatterplot3d, plotly, testthat (>= 3.0.0), knitr, rmarkdown Oldemar Rodríguez Rojas <oldemar.rodriguez@ucr.ac.cr> Comprehensive R Archive Network (CRAN) Oldemar Rodríguez Rojas [aut, cre], Jennifer Lobo Vásquez [aut] BSD_3_clause + file LICENSE (https://CRAN.R-project.org/package=riemannianStats/LICENSE) 2026-07-23 application/tgz https://CRAN.R-project.org/package=riemannianStats doi:10.32614/CRAN.package.riemannianStats en-US