BFI: Bayesian Federated Inference

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, logistic and survival regression models. For GLMs, see Jonker, Pazira and Coolen (2024) <doi:10.1002/sim.10072>; for survival models, see Pazira, Massa, Weijers, Coolen and Jonker (2024) <doi:10.48550/arXiv.2404.17464>; and for heterogeneous populations, see Jonker, Pazira and Coolen (2024) <doi:10.48550/arXiv.2402.02898>.

Version: 2.0.1
Depends: R (≥ 2.10)
Imports: stats
Suggests: knitr, rmarkdown, roxygen2, devtools, spelling, testthat (≥ 3.0.0)
Published: 2024-07-04
DOI: 10.32614/CRAN.package.BFI
Author: Hassan Pazira ORCID iD [aut, cre], Emanuele Massa ORCID iD [aut], Marianne A. Jonker ORCID iD [aut]
Maintainer: Hassan Pazira <hassan.pazira at>
License: MIT + file LICENSE
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
Using BFI in SAS


Package source: BFI_2.0.1.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release (arm64): BFI_2.0.1.tgz, r-oldrel (arm64): BFI_2.0.1.tgz, r-release (x86_64): BFI_2.0.1.tgz, r-oldrel (x86_64): BFI_2.0.1.tgz
Old sources: BFI archive


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