riemannianStats
0.2.0Riemannian Methods for Principal Component Analysis, Regression and Visualization
Overview
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.
Install
Health
- OK2026-07-187 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
Documentation
- Examples that run
- 95%
- Documented parameters
- 100%
- Return-value docs
- 100%
- References docs
- 0%
Downloads
Dependencies
Nothing depends on this yet.
Code & Tests
People & History
2 releases. Pick two to compare their code metrics. R releases are shown for context.
- 0.2.0Latest
- 0.1.12026-07-17
- RR 4.6.0 released · 2026-04-24
Package metadata
- First published
- 2026-07-17
- Total releases
- 2 / 1 yrs
- License
- BSD_3_clause + file LICENSE OSI
- Minimum R
- ≥ 4.1
- Download size
- not tracked yet
- Installed size
- not tracked yet
- With dependencies
- not tracked yet