The Bayesian Federated Inference ('BFI') method combines inference results obtained from local data sets in the separate centers. In this version of the package, the 'BFI' methodology is programmed for linear and logistic regression models; see Jonker, Pazira and Coolen (2024) <doi:10.1002/sim.10072>.
Version: | 1.1.4 |
Depends: | R (≥ 2.10) |
Imports: | devtools, stats |
Suggests: | knitr, rmarkdown, roxygen2, spelling, testthat (≥ 3.0.0) |
Published: | 2024-04-27 |
DOI: | 10.32614/CRAN.package.BFI |
Author: | Hassan Pazira [aut, cre], Emanuele Massa [aut], Marianne A. Jonker [aut] |
Maintainer: | Hassan Pazira <hassan.pazira at radboudumc.nl> |
License: | MIT + file LICENSE |
URL: | https://hassanpazira.github.io/BFI/ |
NeedsCompilation: | no |
Language: | en-US |
Citation: | BFI citation info |
Materials: | README NEWS |
CRAN checks: | BFI results |
Reference manual: | BFI.pdf |
Vignettes: |
An Introduction to BFI Calling BFI from Python Calling BFI from SAS |
Package source: | BFI_1.1.4.tar.gz |
Windows binaries: | r-devel: BFI_1.1.4.zip, r-release: BFI_1.1.4.zip, r-oldrel: BFI_1.1.4.zip |
macOS binaries: | r-release (arm64): BFI_1.1.4.tgz, r-oldrel (arm64): BFI_1.1.4.tgz, r-release (x86_64): BFI_1.1.4.tgz, r-oldrel (x86_64): BFI_1.1.4.tgz |
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