Package: hdbma 1.0

Qingzhao Yu

hdbma: Bayesian Mediation Analysis with High-Dimensional Data

Mediation analysis is used to identify and quantify intermediate effects from factors that intervene the observed relationship between an exposure/predicting variable and an outcome. We use a Bayesian adaptive lasso method to take care of the hierarchical structures and high dimensional exposures or mediators.

Authors:Qingzhao Yu [aut, cre, cph], Bin Li [aut]

hdbma_1.0.tar.gz
hdbma_1.0.tar.gz(r-4.7-any)hdbma_1.0.tar.gz(r-4.6-any)
hdbma_1.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
hdbma/json (API)

# Install 'hdbma' in R:
install.packages('hdbma', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))
Uses libs:
  • jags– Just Another Gibbs Sampler for Bayesian MCMC - binary JAGS is Just Another Gibbs Sampler. It is a program for analysis of Bayesian hierarchical models using Markov Chain Monte Carlo (MCMC) simulation not wholly unlike BUGS. JAGS was written with three aims in mind: * To have an engine for the BUGS language that runs on Unix * To be extensible, allowing users to write their own functions, distributions and samplers. * To be a plaftorm for experimentation with ideas in Bayesian modelling This package contains the 'jags' binary as well as the associated shared library modules loaded by the binary.
  • c++– GNU Standard C++ Library v3
Datasets:

On CRAN:

Conda:

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

jagscpp

1.00 score 194 downloads 3 exports 23 dependencies

Last updated from:a2d64d2fe9. Checks:4 OK. Indexed: no.

TargetResultTimeFilesSyslog
linux-devel-x86_64OK131
source / vignettesOK179
linux-release-x86_64OK135
wasm-releaseOK104

Exports:hdbmaprint.summary.hdbmasummary.hdbma

Dependencies:abindbitopsbootcaToolsclicodagluegplotsgtoolsKernSmoothlatticelifecyclemagrittrMASSMatrixR2jagsR2WinBUGSrjagsrlangstringistringrsurvivalvctrs