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Riemann: Learning with Data on Riemannian Manifolds
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.
| Version: |
0.1.4 |
| Depends: |
R (≥ 2.10) |
| Imports: |
CVXR, Rcpp (≥ 1.0.5), Rdpack, RiemBase, Rdimtools, T4cluster, DEoptim, lpSolve, Matrix, maotai (≥ 0.2.2), stats, utils |
| LinkingTo: |
Rcpp, RcppArmadillo |
| Suggests: |
R.rsp, knitr, rmarkdown |
| Published: |
2022-02-28 |
| DOI: |
10.32614/CRAN.package.Riemann |
| Author: |
Kisung You  [aut,
cre] |
| Maintainer: |
Kisung You <kisungyou at outlook.com> |
| BugReports: |
https://github.com/kisungyou/Riemann/issues |
| License: |
MIT + file LICENSE |
| URL: |
https://kisungyou.com/Riemann/ |
| NeedsCompilation: |
yes |
| Materials: |
README NEWS |
| CRAN checks: |
Riemann results |
Documentation:
Downloads:
Linking:
Please use the canonical form
https://CRAN.R-project.org/package=Riemann
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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.