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dppca

0.1.0Package record

Differentially Private Principal Component Analysis Visualization

0packages depend
1.6Kdownloads / year
–test coverage
13/13flavors OK

Overview

About

Provides tools for differentially private principal component analysis (PCA) visualization. It includes functions for estimating private principal component directions, constructing private scree and proportion of variance explained summaries, and visualizing two-dimensional PCA score summaries using additive and sparse histogram mechanisms. Group-wise score visualizations and an interactive 'shiny' app are also provided. Private principal component directions are based on Kim and Jung (2025) doi:10.1002/sam.70053. Private scree summaries use mechanisms motivated by Dwork and Roth (2014) doi:10.1561/0400000042, Ramsay and Spicker (2025) doi:10.48550/arXiv.2501.14095, and Yu, Ren and Zhou (2024) doi:10.3150/23-BEJ1706. Private score plot frames use smooth sensitivity quantiles from Nissim, Raskhodnikova and Smith (2007) doi:10.1145/1250790.1250803. Private score histograms use additive and sparse histogram ideas from Wasserman and Zhou (2010) doi:10.1198/jasa.2009.tm08651 and Karwa and Vadhan (2018) doi:10.4230/LIPIcs.ITCS.2018.44.

Install

Health

CRAN checks
13OK
Slowest check: 2.1 min · r-oldrel-windows-x86_64
Status changes
  • OK13 OK2026-08-05
  • NOTE12 OK, 1 NOTE2026-08-01
  • OK7 OK2026-06-05
Advisories

none known

Documentation

In release 0.1.0
READMEYes · 685 wordsVignettesYes · 5 · dynamicNEWSNoCitation fileNoWebsiteYes · pkgdown
Help pages
15 (1 internal)includes a package overview page
Examples that run
100%11 run in a plain check (1 of them under a condition)
Exported functions with examples
100%
Documented parameters
94%
Return-value docs
100%
Help pages citing references
53% with a bibliography file

Downloads

1.6K
CRAN downloads in the past year
Rank #13,153 · ~4/day · ~130/mo
Daily download trend is not available in this view yet.
32330 days
87690 days
1.6K1 year
Compare downloads with other packages →
Also on29 r2u1 autocran

Repository

2Stars
0Forks
0Open issues
0Open PRs
0Releases
85Commits
3Commit identities
85 commits · Last activity 2026-10-17 · 0% stars, 30d · Default branch at 0.1.0.9000, ahead of CRAN 0.1.0 (checked 2026-10-21)
Responsiveness
How these are sampled
PRs merged (all time)
100%
Median days to close, 50 most recently updated closed issues
not measured
Median days to close, 50 most recently updated closed PRs
0

Stars over time

2025-12-13 · 12026-07-07 · 2
PracticesBeta

4 development-tooling and community-health practices detected across 3 families in the upstream repository

Checks run against github.com/yejinjo0220/dppca on 2026-10-21.

Docs source (2)
pkgdown

GitHub Pages site last deployed 2026-10-17

pkgdown site last built 2026-05-31, before release 0.1.0 (2026-06-04)

Reproducibility and dev environment (1)
data-raw/
Lint, format, editor (1)
RStudio project
How this is detected·Detection ruleset v4 (2026-10-20)

Dependencies

Declared dependencies
10 external dependencies (excludes base and recommended)

Installing dppca adds 33 packages (17 with compiled code, 26 MB of source tarballs). Heaviest: ggplot2 6.0 MB, patchwork 3.2 MB, Rcpp 1.8 MB.

Depends (1)
R >= 4.3.0
Imports (10)
LinkingTo (0)
none
Enhances (0)
none
Reverse dependencies
0direct
0indirect

Nothing depends on this yet.

Datasets

People & History

People (2)
Author, Maintainer since 0.1.0 (2026)
Releases (1)
  • 0.1.0Latest
    2026-06-04 · current release
  • R
    R 4.6.0 released · 2026-04-24

Package metadata

First published
2026-06-04
Total releases
1 / 1 yrs
License
MIT + file LICENSE OSI
Minimum R
≥ 4.3.0
Bundled data
1.5 MB / 3 files
Download size
3.4 MB

Cite

Cite this package

Run in R for the authors' preferred citation:

citation("dppca")
Jo, Y., & Kim, M. (2026). dppca: Differentially Private Principal Component Analysis Visualization (Version 0.1.0) [Computer software]. https://doi.org/10.32614/CRAN.package.dppca

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 dppca version 0.1.0 [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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