A novel sufficient-dimension reduction method is robust against outliers using alpha-distance covariance and manifold-learning in dimensionality reduction problems. Please refer Hsin-Hsiung Huang, Feng Yu & Teng Zhang (2024) <doi:10.1080/10485252.2024.2313137> for the details.
| Version: | 1.0.2.1 | 
| Imports: | expm, ManifoldOptim, methods, Rcpp, rstiefel, scatterplot3d, future, future.apply, ggplot2, ggsci | 
| Suggests: | knitr, rmarkdown, Matrix, RcppNumerical, fdm2id | 
| Published: | 2025-10-28 | 
| DOI: | 10.32614/CRAN.package.rSDR (may not be active yet) | 
| Author: | Sheau-Chiann Chen  [aut, cre],
  Shilin Zhao [aut],
  Hsin-Hsiung Bill Huang  [aut] | 
| Maintainer: | Sheau-Chiann Chen  <sheau-chiann.chen.1 at vumc.org> | 
| License: | GPL (≥ 3) | 
| NeedsCompilation: | no | 
| CRAN checks: | rSDR results |