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rsvddpd

1.0.1Package record

Robust Singular Value Decomposition using Density Power Divergence

0packages depend
3Kdownloads / year
–test coverage
13/13flavors OK

Overview

About

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.

Changes in 1.0.1
  • Added a new function rank.rSVDdpd which is used to determine the rank for matrix factorization. This is internally applied to the existing function rSVDdpd for automatic matrix rank determination.

From NEWS.md in the release

Install

Health

CRAN checks
13OK
Slowest check: 3.0 min · r-devel-windows-x86_64
Status changes
  • OK13 OK2026-08-04
  • NOTE12 OK, 1 NOTE2026-08-01
  • OK14 OK2026-04-22
  • ERROR13 OK, 1 ERROR2026-04-18
  • OK14 OK2026-03-10
Advisories

none known

Documentation

In release 1.0.1
READMEYes · 312 wordsVignettesYes · 1 · dynamicNEWSYes · 67% structured · mentions 1.0.1Citation fileNoWebsitenot declared in DESCRIPTION
Help pages
5
Examples that run
100%3 run in a plain check
Exported functions with examples
60%
Documented parameters
not tracked
Return-value docs
not tracked
Help pages citing references
40%

Downloads

3K
CRAN downloads in the past year
Rank #16,857 · ~8/day · ~246/mo
Daily download trend is not available in this view yet.
28930 days
75590 days
3K1 year
Compare downloads with other packages →
Also on341 r2u1 autocran

Repository

4Stars
0Forks
0Open issues
0Open PRs
0Releases
23Commits
1Commit identities
r-packageresearch-projectrobust-pcavideo-background-filter
23 commits · Last activity 2025-09-20
Responsiveness
not measured
PracticesBeta

5 development-tooling and community-health practices detected across 4 families in the upstream repository

Checks run against github.com/subroy13/rsvddpd on 2026-10-22.

Continuous integration (2)
GitHub ActionsR CMD check workflow

The R CMD check workflow runs on Linux, macOS and Windows, and on R-devel

Docs source (1)
README.Rmd
CRAN release process (1)
cran-comments.md
Lint, format, editor (1)
lintr
How this is detected·Detection ruleset v4 (2026-10-20)

Dependencies

Declared dependencies
9 external dependencies (excludes base and recommended)

Installing rsvddpd adds 3 packages (3 with compiled code, 3.0 MB of source tarballs). Heaviest: Rcpp 1.8 MB, RcppArmadillo 1.0 MB, matrixStats 207 KB.

Depends (0)
none
Imports (5)
RcppMASSstatsutilsmatrixStats
LinkingTo (2)
Enhances (0)
none
Reverse dependencies
0direct
0indirect

Nothing depends on this yet.

People & History

People (1)
Author, Maintainer since 1.0.0 (2021)
Releases (2)

Pick two releases to compare their code metrics.

  • R
    R 4.6.0 released · 2026-04-24
  • 1.0.1Latest
    record
    2025-09-20 · current release · diff ↗
  • R
    R 4.5.0 released · 2025-04-11
  • R
    R 4.4.0 released · 2024-04-24
  • R
    R 4.3.0 released · 2023-04-21
  • R
    R 4.2.0 released · 2022-04-22
  • 1.0.0
    record
    2021-10-27
  • R
    R 4.1.0 released · 2021-05-18

Package metadata

First published
2021-10-27
Total releases
2 / 5 yrs
License
MIT + file LICENSE OSI
Download size
32 KB

Cite

Cite this package

Run in R for the authors' preferred citation:

citation("rsvddpd")
Roy, S. (2025). rsvddpd: Robust Singular Value Decomposition using Density Power Divergence (Version 1.0.1) [Computer software]. https://doi.org/10.32614/CRAN.package.rsvddpd

This package has no citation file, so citation() returns this entry built from DESCRIPTION.

Cite the R Observatory

For a number measured here: a download total, a coverage figure, an archival date.

APA

Balamuta, J. J. (2026). R Observatory: Metrics for rsvddpd version 1.0.1 [Data set]. HJJB, LLC. Data release v2026-10-25. https://doi.org/10.5281/zenodo.21843040

From data release v2026-10-25, which the citation names so these numbers can be found later. More on citing and the projects behind them.

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