Package: fkbma 0.2.0

Lara Maleyeff

fkbma: Free Knot-Bayesian Model Averaging

Analysis of Bayesian adaptive enrichment clinical trial using Free-Knot Bayesian Model Averaging (FK-BMA) method of Maleyeff et al. (2024) for Gaussian data. Maleyeff, L., Golchi, S., Moodie, E. E. M., & Hudson, M. (2024) "An adaptive enrichment design using Bayesian model averaging for selection and threshold-identification of predictive variables" <doi:10.1093/biomtc/ujae141>.

Authors:Lara Maleyeff [aut, cre], Shirin Golchi [aut], Erica E. M. Moodie [aut]

fkbma_0.2.0.tar.gz
fkbma_0.2.0.tar.gz(r-4.5-noble)fkbma_0.2.0.tar.gz(r-4.4-noble)
fkbma_0.2.0.tgz(r-4.4-emscripten)fkbma_0.2.0.tgz(r-4.3-emscripten)
fkbma.pdf |fkbma.html✨
fkbma/json (API)

# Install 'fkbma' in R:
install.packages('fkbma', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))
Datasets:
  • simulated_data - A synthetic dataset with continuous and binary covariates and a binary treatment variable ('trt').

On CRAN:

Conda:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

1.30 score 567 downloads 7 exports 56 dependencies

Last updated 17 days agofrom:5bc428e356. Checks:3 OK. Indexed: yes.

TargetResultLatest binary
Doc / VignettesOKMar 06 2025
R-4.5-linuxOKMar 06 2025
R-4.4-linuxOKMar 06 2025

Exports:credintfittedExposureEffgetEffectiveSubspacepippredictExposureEffrhatsrjMCMC

Dependencies:abindbackportsBHcallrcheckmateclicodacolorspacecowplotdescdistributionaldplyrfansifarvergenericsggplot2gluegridExtragtableinlineisobandlabelinglatticelifecycleloomagrittrMASSMatrixmatrixStatsmgcvmunsellnlmenumDerivpillarpkgbuildpkgconfigposteriorprocessxpsQuickJSRR6RColorBrewerRcppRcppEigenRcppParallelrlangrstanscalesStanHeaderstensorAtibbletidyselectutf8vctrsviridisLitewithr