Description
Learning with Data on Riemannian Manifolds.
Description
We provide a variety of algorithms for manifold-valued data, including Fréchet summaries, hypothesis testing, clustering, visualization, and other learning tasks. See Bhattacharya and Bhattacharya (2012) <doi:10.1017/CBO9781139094764> for general exposition to statistics on manifolds.
README.md
Riemann 
Riemann is an R package for learning with data on Riemannian manifolds. In statistics and machine learning, the term manifold appears in two realms; one is dimensionality reduction where we assume that low-dimensional data manifold is embedded in high-dimensional Euclidean space. The other is statistics on manifolds - data lie on some Riemannian manifolds that we are already well aware of. Riemann aims to achieve the latter. If you are interested in dimension reduction, please check another R package Rdimtools.
Installation
- Option 1 : released version from CRAN.
install.packages("Riemann")
- Option 2 : development version from GitHub.
if (!require("devtools")) {
install.packages("devtools")
}
devtools::install_github("kisungyou/Riemann")