Package: rsvddpd 1.0.0
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.zip(r-4.5)rsvddpd_1.0.0.zip(r-4.4)rsvddpd_1.0.0.zip(r-4.3)
rsvddpd_1.0.0.tgz(r-4.5-x86_64)rsvddpd_1.0.0.tgz(r-4.5-arm64)rsvddpd_1.0.0.tgz(r-4.4-x86_64)rsvddpd_1.0.0.tgz(r-4.4-arm64)rsvddpd_1.0.0.tgz(r-4.3-x86_64)rsvddpd_1.0.0.tgz(r-4.3-arm64)
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://subroy13.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/subroy13/rsvddpd/issues
Last updated 2 years agofrom:86685f2ea2. Checks:1 OK, 10 NOTE. Indexed: yes.
Target | Result | Latest binary |
---|---|---|
Doc / Vignettes | OK | Jan 31 2025 |
R-4.5-win-x86_64 | NOTE | Jan 31 2025 |
R-4.5-mac-x86_64 | NOTE | Jan 31 2025 |
R-4.5-mac-aarch64 | NOTE | Jan 31 2025 |
R-4.5-linux-x86_64 | NOTE | Jan 31 2025 |
R-4.4-win-x86_64 | NOTE | Jan 31 2025 |
R-4.4-mac-x86_64 | NOTE | Jan 31 2025 |
R-4.4-mac-aarch64 | NOTE | Jan 31 2025 |
R-4.3-win-x86_64 | NOTE | Jan 31 2025 |
R-4.3-mac-x86_64 | NOTE | Jan 31 2025 |
R-4.3-mac-aarch64 | NOTE | Jan 01 2025 |
Exports:AddOutliercv.alpharSVDdpdsimSVD
Dependencies:MASSmatrixStatsRcppRcppArmadillo