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.zip(r-4.7-any)fkbma_0.2.0.zip(r-4.6-any)
fkbma_0.2.0.tar.gz(r-4.7-any)fkbma_0.2.0.tar.gz(r-4.6-any)
fkbma_0.2.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
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.

1.00 score 379 downloads 7 exports 53 dependencies

Last updated from:5bc428e356. Checks:6 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-develOK178
source / vignettesOK187
linux-releaseOK247
windows-develOK153
windows-releaseOK161
wasm-releaseOK192

Exports:credintfittedExposureEffgetEffectiveSubspacepippredictExposureEffrhatsrjMCMC

Dependencies:abindbackportsBHcallrcheckmateclicodacowplotcpp11descdistributionaldplyrfarvergenericsggplot2gluegridExtragtableinlineisobandlabelinglatticelifecycleloomagrittrMASSmatrixStatsnumDerivotelpillarpkgbuildpkgconfigposteriorprocessxpsQuickJSRR6RColorBrewerRcppRcppEigenRcppParallelrlangrstanS7scalesStanHeaderstensorAtibbletidyselectutf8vctrsviridisLitewithr