Package: riemannianStats
Type: Package
Title: Riemannian Methods for Principal Component Analysis, Regression
        and Visualization
Version: 0.2.0
Authors@R: c(
    person(
        given = "Oldemar",
        family = "Rodríguez Rojas",
        email = "oldemar.rodriguez@ucr.ac.cr",
        role = c("aut", "cre")
    ),
    person(
        given = "Jennifer",
        family = "Lobo Vásquez",
        email = "jennifer.lobo@promidat.com",
        role = c("aut")
    )
  )
Description: 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>.
License: BSD_3_clause + file LICENSE
Encoding: UTF-8
Language: en-US
Depends: R (>= 4.1)
Imports: rlang, ggplot2, ggrepel, grid, uwot, vegan, dbscan
Suggests: scatterplot3d, plotly, testthat (>= 3.0.0), knitr, rmarkdown
Config/testthat/edition: 3
VignetteBuilder: knitr, rmarkdown
Config/roxygen2/version: 8.0.0
NeedsCompilation: no
Packaged: 2026-07-22 15:20:32 UTC; r3291508
Author: Oldemar Rodríguez Rojas [aut, cre],
  Jennifer Lobo Vásquez [aut]
Maintainer: Oldemar Rodríguez Rojas <oldemar.rodriguez@ucr.ac.cr>
Repository: CRAN
Date/Publication: 2026-07-23 15:50:09 UTC
Built: R 4.5.3; ; 2026-08-10 03:30:05 UTC; windows
