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A collection of privacy-preserving distributed algorithms (PDAs) for conducting federated statistical learning across multiple data sites. The PDA framework includes models for various tasks such as regression, trial emulation, causal inference, design-specific analysis, and clustering. The PDA algorithms run on a lead site and only require summary statistics from collaborating sites, with one or few iterations. The package can be used together with the online data transfer system (<https://pda-ota.pdamethods.org/>) for safe and convenient collaboration. For more information, please visit our software websites: <https://github.com/Penncil/pda>, and <https://pdamethods.org/>.
| Version: | 1.3.0 |
| Depends: | R (≥ 4.1.0) |
| Imports: | Rcpp (≥ 0.12.19), stats, httr, rvest, jsonlite, data.table, cobalt, EmpiricalCalibration, survival, minqa, glmnet, MASS, numDeriv, metafor, Matrix, ordinal, plyr, tidyr, tibble, dplyr, geex, data.tree |
| LinkingTo: | Rcpp, RcppArmadillo, RcppEigen |
| Suggests: | lme4 |
| Published: | 2025-11-17 |
| DOI: | 10.32614/CRAN.package.pda |
| Author: | Chongliang Luo [cre], Rui Duan [aut], Mackenzie Edmondson [aut], Jiayi Tong [aut], Xiaokang Liu [aut], Kenneth Locke [aut], Jie Hu [aut], Bingyu Zhang [aut], Yicheng Shen [aut], Yudong Wang [aut], Yiwen Lu [aut], Lu Li [aut], Yong Chen [aut], Penn Computing Inference Learning (PennCIL) lab [cph] |
| Maintainer: | Chongliang Luo <luocl3009 at gmail.com> |
| License: | Apache License 2.0 |
| NeedsCompilation: | yes |
| Materials: | NEWS |
| CRAN checks: | pda results |
| Reference manual: | pda.html , pda.pdf |
| Package source: | pda_1.3.0.tar.gz |
| Windows binaries: | r-devel: pda_1.2.8.zip, r-release: pda_1.2.8.zip, r-oldrel: pda_1.2.8.zip |
| macOS binaries: | r-release (arm64): pda_1.2.8.tgz, r-oldrel (arm64): pda_1.2.8.tgz, r-release (x86_64): pda_1.3.0.tgz, r-oldrel (x86_64): pda_1.3.0.tgz |
| Old sources: | pda archive |
Please use the canonical form https://CRAN.R-project.org/package=pda 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.
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