rsvddpd: Robust Singular Value Decomposition using Density PowerDivergence
Computing singular value decomposition with robustness is a challenging task. This package provides an implementation of computing robust SVD using density power divergence (<doi:10.48550/arXiv.2109.10680>). It combines the idea of robustness and efficiency in estimation based on a tuning parameter. It also provides utility functions to simulate various scenarios to compare performances of different algorithms.
| Version: | 1.0.1 |
| Imports: | Rcpp (≥ 1.0.5),MASS, stats, utils,matrixStats |
| LinkingTo: | Rcpp,RcppArmadillo |
| Suggests: | knitr,rmarkdown,microbenchmark,pcaMethods,V8 |
| Published: | 2025-09-20 |
| DOI: | 10.32614/CRAN.package.rsvddpd |
| Author: | Subhrajyoty Roy [aut, cre] |
| Maintainer: | Subhrajyoty Roy <subhrajyotyroy at gmail.com> |
| BugReports: | https://github.com/subroy13/rsvddpd/issues |
| License: | MIT + fileLICENSE |
| URL: | https://github.com/subroy13/rsvddpd |
| NeedsCompilation: | yes |
| Materials: | README,NEWS |
| CRAN checks: | rsvddpd results |
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