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 |