The hardware and bandwidth for this mirror is donated by dogado GmbH, the Webhosting and Full Service-Cloud Provider. Check out our Wordpress Tutorial.
If you wish to report a bug, or if you are interested in having us mirror your free-software or open-source project, please feel free to contact us at mirror[@]dogado.de.
Implements two differentially private algorithms for estimating L2-regularized logistic regression coefficients. A randomized algorithm F is epsilon-differentially private (C. Dwork, Differential Privacy, ICALP 2006 <doi:10.1007/11681878_14>), if |log(P(F(D) in S)) - log(P(F(D') in S))| <= epsilon for any pair D, D' of datasets that differ in exactly one record, any measurable set S, and the randomness is taken over the choices F makes.
| Version: | 1.2-22 |
| Published: | 2018-03-20 |
| DOI: | 10.32614/CRAN.package.PrivateLR |
| Author: | Staal A. Vinterbo |
| Maintainer: | Staal A. Vinterbo <Staal.Vinterbo at ntnu.no> |
| License: | GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
| NeedsCompilation: | no |
| CRAN checks: | PrivateLR results |
| Reference manual: | PrivateLR.pdf |
| Package source: | PrivateLR_1.2-22.tar.gz |
| Windows binaries: | r-devel: PrivateLR_1.2-22.zip, r-release: PrivateLR_1.2-22.zip, r-oldrel: PrivateLR_1.2-22.zip |
| macOS binaries: | r-release (arm64): PrivateLR_1.2-22.tgz, r-oldrel (arm64): PrivateLR_1.2-22.tgz, r-release (x86_64): PrivateLR_1.2-22.tgz, r-oldrel (x86_64): PrivateLR_1.2-22.tgz |
| Old sources: | PrivateLR archive |
Please use the canonical form https://CRAN.R-project.org/package=PrivateLR to link to this page.
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
Health stats visible at Monitor.