Package: fdp 1.0.0

fdp: f-Differential Privacy and Gaussian Differential Privacy

Constructs and visualises trade-off functions for f-differential privacy (f-DP) as introduced by Dong et al. (2022) <doi:10.1111/rssb.12454>. Supports Gaussian differential privacy, the f-DP generalisation of (epsilon, delta)-differential privacy, and accepts user-specified optimal type I / type II errors from which the lower convex hull trade-off function is automatically constructed.

Authors:Louis Aslett [aut, cre, cph]

fdp_1.0.0.tar.gz
fdp_1.0.0.zip(r-4.7-any)fdp_1.0.0.zip(r-4.6-any)fdp_1.0.0.zip(r-4.5-any)
fdp_1.0.0.tgz(r-4.6-any)fdp_1.0.0.tgz(r-4.5-any)
fdp_1.0.0.tar.gz(r-4.7-any)fdp_1.0.0.tar.gz(r-4.6-any)
fdp_1.0.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
fdp/json (API)

# Install 'fdp' in R:
install.packages('fdp', repos = c('https://louisaslett.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/louisaslett/fdp/issues

Pkgdown/docs site:https://fdp.louisaslett.com

On CRAN:

Conda:

3.40 score 1 scripts 261 downloads 11 exports 17 dependencies

Last updated from:65fdd6c157. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-x86_64OK125
source / vignettesOK204
linux-release-x86_64OK137
macos-release-arm64OK183
macos-oldrel-arm64OK144
windows-develOK80
windows-releaseOK74
windows-oldrelOK76
wasm-releaseOK96

Exports:epsdeltaest_epsdeltaest_gdpfdpfdp_attributesfdp_linefdp_namefdp_pointgdpgdp_to_epsdeltalap

Dependencies:clicpp11farverggplot2gluegtableisobandlabelinglifecycleR6RColorBrewerrlangS7scalesvctrsviridisLitewithr