Package: SurrogateBMA 1.0

SurrogateBMA: Flexible Evaluation of Surrogate Markers with Bayesian Model Averaging

Provides functions to estimate the proportion of treatment effect explained by the surrogate marker using a Bayesian Model Averaging approach. Duan and Parast (2023) <doi:10.1002/sim.9986>.

Authors:Yunshan Duan [aut, cre], Layla Parast [aut]

SurrogateBMA_1.0.tar.gz
SurrogateBMA_1.0.zip(r-4.5)SurrogateBMA_1.0.zip(r-4.4)SurrogateBMA_1.0.zip(r-4.3)
SurrogateBMA_1.0.tgz(r-4.5-x86_64)SurrogateBMA_1.0.tgz(r-4.5-arm64)SurrogateBMA_1.0.tgz(r-4.4-x86_64)SurrogateBMA_1.0.tgz(r-4.4-arm64)SurrogateBMA_1.0.tgz(r-4.3-x86_64)SurrogateBMA_1.0.tgz(r-4.3-arm64)
SurrogateBMA_1.0.tar.gz(r-4.5-noble)SurrogateBMA_1.0.tar.gz(r-4.4-noble)
SurrogateBMA_1.0.tgz(r-4.4-emscripten)SurrogateBMA_1.0.tgz(r-4.3-emscripten)
SurrogateBMA.pdf |SurrogateBMA.html✨
SurrogateBMA/json (API)

# Install 'SurrogateBMA' in R:
install.packages('SurrogateBMA', repos = c('https://yunshandys.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/yunshandys/surrogatebma/issues

Uses libs:
  • c++– GNU Standard C++ Library v3
Datasets:

On CRAN:

Conda:

cpp

2.70 score 126 downloads 11 exports 15 dependencies

Last updated 1 years agofrom:60a8a205d2. Checks:12 OK. Indexed: yes.

TargetResultLatest binary
Doc / VignettesOKMar 31 2025
R-4.5-win-x86_64OKMar 31 2025
R-4.5-mac-x86_64OKMar 31 2025
R-4.5-mac-aarch64OKMar 31 2025
R-4.5-linux-x86_64OKMar 31 2025
R-4.4-win-x86_64OKMar 31 2025
R-4.4-mac-x86_64OKMar 31 2025
R-4.4-mac-aarch64OKMar 31 2025
R-4.4-linux-x86_64OKMar 31 2025
R-4.3-win-x86_64OKMar 31 2025
R-4.3-mac-x86_64OKMar 31 2025
R-4.3-mac-aarch64OKMar 31 2025

Exports:cv.npfpred.intgen.priorgpxi_intpost.modelpost.thetapred.funcR.BMA.estR.BMAonlyR.m.thetarcpp_hello_world

Dependencies:codalatticeMASSMatrixMatrixModelsmcmcMCMCpackmvtnormquantregRcppRcppEigenRcppNumericalRsurrogateSparseMsurvival