doi:10.1080/10485252.2024.2313137> for the details.">

rSDR: Robust Sufficient Dimension Reduction (original) (raw)

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 ORCID iD [aut, cre], Shilin Zhao [aut], Hsin-Hsiung Bill HuangORCID iD [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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