Package: rsvddpd 1.0.0
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 (<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_1.0.0.tar.gz
rsvddpd_1.0.0.tar.gz(r-4.5-noble)rsvddpd_1.0.0.tar.gz(r-4.4-noble)
rsvddpd_1.0.0.tgz(r-4.4-emscripten)rsvddpd_1.0.0.tgz(r-4.3-emscripten)
rsvddpd.pdf |rsvddpd.html✨
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 3 years agofrom:284be1c1bb. Checks:OK: 1 NOTE: 1. Indexed: no.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Dec 27 2024 |
| R-4.5-linux-x86_64 | NOTE | Dec 27 2024 |
Exports:AddOutliercv.alpharSVDdpdsimSVD
Dependencies:MASSmatrixStatsRcppRcppArmadillo
