rSDR: Robust Sufficient Dimension Reduction
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: | 1.0.3.0 |
| Imports: | ManifoldOptim, methods,Rcpp,rstiefel,scatterplot3d,future,future.apply,ggplot2,ggsci |
| Suggests: | expm,knitr,rmarkdown,Matrix,RcppNumerical,fdm2id |
| Published: | 2025-11-10 |
| DOI: | 10.32614/CRAN.package.rSDR |
| 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 |
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