DPpack: Differentially Private Statistical Analysis and Machine Learning

An implementation of common statistical analysis and models with differential privacy (Dwork et al., 2006a) <doi:10.1007/11681878_14> guarantees. The package contains, for example, functions providing differentially private computations of mean, variance, median, histograms, and contingency tables. It also implements some statistical models and machine learning algorithms such as linear regression (Kifer et al., 2012) <https://proceedings.mlr.press/v23/kifer12.html> and SVM (Chaudhuri et al., 2011) <https://jmlr.org/papers/v12/chaudhuri11a.html>. In addition, it implements some popular randomization mechanisms such as the Laplace mechanism (Dwork et al., 2006a) <doi:10.1007/11681878_14>, Gaussian mechanism (Dwork et al., 2006b) <doi:10.1007/11761679_29>, and exponential mechanism (McSherry & Talwar, 2007) <doi:10.1109/FOCS.2007.66>.

Version: 0.0.1
Imports: rmutil (≥ 1.1.5), Rdpack (≥ 2.1.2), R6 (≥ 2.5.1), dplyr (≥ 1.0.1), MASS (≥ 7.3-51.6), nloptr (≥ 1.2.2.2), e1071 (≥ 1.7-9), stats (≥ 4.0.2), graphics (≥ 4.0.2), ggplot2 (≥ 3.3.2)
Suggests: testthat (≥ 3.0.0)
Published: 2022-04-28
Author: Spencer Giddens with contributions from Fang Liu
Maintainer: Spencer Giddens <giddens2spencer at gmail.com>
License: GPL-3
NeedsCompilation: no
Materials: README
CRAN checks: DPpack results

Documentation:

Reference manual: DPpack.pdf

Downloads:

Package source: DPpack_0.0.1.tar.gz
Windows binaries: r-devel: DPpack_0.0.1.zip, r-release: DPpack_0.0.1.zip, r-oldrel: DPpack_0.0.1.zip
macOS binaries: r-release (arm64): DPpack_0.0.1.tgz, r-oldrel (arm64): DPpack_0.0.1.tgz, r-release (x86_64): DPpack_0.0.1.tgz, r-oldrel (x86_64): DPpack_0.0.1.tgz

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