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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: | 1.0.0 |
| Imports: | Rcpp (≥ 1.0.5), MASS, stats, utils, matrixStats |
| LinkingTo: | Rcpp, RcppArmadillo |
| Suggests: | knitr, rmarkdown, microbenchmark, pcaMethods |
| Published: | 2021-10-27 |
| Author: | Subhrajyoty Roy [aut, cre] |
| Maintainer: | Subhrajyoty Roy <subhrajyotyroy at gmail.com> |
| BugReports: | https://github.com/subroy13/rsvddpd/issues |
| License: | MIT + file LICENSE |
| URL: | https://github.com/subroy13/rsvddpd |
| NeedsCompilation: | yes |
| Materials: | README NEWS |
| CRAN checks: | rsvddpd results |
| Reference manual: | rsvddpd.pdf |
| Vignettes: |
Introduction to rSVDdpd |
| Package source: | rsvddpd_1.0.0.tar.gz |
| Windows binaries: | r-devel: rsvddpd_1.0.0.zip, r-release: rsvddpd_1.0.0.zip, r-oldrel: rsvddpd_1.0.0.zip |
| macOS binaries: | r-release (arm64): rsvddpd_1.0.0.tgz, r-oldrel (arm64): rsvddpd_1.0.0.tgz, r-release (x86_64): rsvddpd_1.0.0.tgz, r-oldrel (x86_64): rsvddpd_1.0.0.tgz |
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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.
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