Package: rsvddpd 1.0.1
Subhrajyoty Roy
rsvddpd: Robust Singular Value Decomposition using Density Power Divergence
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.
Authors:
rsvddpd_1.0.1.tar.gz
rsvddpd_1.0.1.tar.gz(r-4.7-arm64)rsvddpd_1.0.1.tar.gz(r-4.7-x86_64)rsvddpd_1.0.1.tar.gz(r-4.6-arm64)rsvddpd_1.0.1.tar.gz(r-4.6-x86_64)
rsvddpd_1.0.1.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
rsvddpd/json (API)
NEWS
| # Install 'rsvddpd' in R: |
| install.packages('rsvddpd', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/subroy13/rsvddpd/issues
Last updated from:f0644eb139. Checks:6 OK. Indexed: no.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel-arm64 | OK | 122 | ||
| linux-devel-x86_64 | OK | 129 | ||
| source / vignettes | OK | 194 | ||
| linux-release-arm64 | OK | 130 | ||
| linux-release-x86_64 | OK | 122 | ||
| wasm-release | OK | 113 |
Exports:AddOutliercv.alpharank.rSVDdpdrSVDdpdsimSVD
Dependencies:MASSmatrixStatsRcppRcppArmadillo
