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.


News

Reference manual

It appears you don't have a PDF plugin for this browser. You can click here to download the reference manual.

install.packages("Riemann")

0.1.3 by Kisung You, a month ago


https://kisungyou.com/Riemann/


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