Learning with Data on Riemannian Manifolds

We provide a variety of algorithms for manifold-valued data, including Fr├ęchet summaries, hypothesis testing, clustering, visualization, and other learning tasks. See Bhattacharya and Bhattacharya (2012) for general exposition to statistics on manifolds.


Reference manual

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0.1.3 by Kisung You, 4 months ago


Report a bug at https://github.com/kisungyou/Riemann/issues

Browse source code at https://github.com/cran/Riemann

Authors: Kisung You [aut, cre]

Documentation:   PDF Manual  

MIT + file LICENSE license

Imports CVXR, Rcpp, Rdpack, RiemBase, Rdimtools, T4cluster, DEoptim, lpSolve, Matrix, maotai, stats, utils, ggrepel

Suggests knitr, rmarkdown, rgdal, usmap, ggplot2, maptools

Linking to Rcpp, RcppArmadillo

See at CRAN