Package: hdbm 0.9.0

Alexander Rix

hdbm: High Dimensional Bayesian Mediation Analysis

Perform mediation analysis in the presence of high-dimensional mediators based on the potential outcome framework. High dimensional Bayesian mediation (HDBM), developed by Song et al (2018) <doi:10.1101/467399>, relies on two Bayesian sparse linear mixed models to simultaneously analyze a relatively large number of mediators for a continuous exposure and outcome assuming a small number of mediators are truly active. This sparsity assumption also allows the extension of univariate mediator analysis by casting the identification of active mediators as a variable selection problem and applying Bayesian methods with continuous shrinkage priors on the effects.

Authors:Alexander Rix [aut, cre], Yanyi Song [aut]

hdbm_0.9.0.tar.gz
hdbm_0.9.0.tar.gz(r-4.5-noble)hdbm_0.9.0.tar.gz(r-4.4-noble)
hdbm_0.9.0.tgz(r-4.4-emscripten)hdbm_0.9.0.tgz(r-4.3-emscripten)
hdbm.pdf |hdbm.html
hdbm/json (API)
NEWS

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

Peer review:

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

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

2.70 score 6 scripts 158 downloads 1 exports 2 dependencies

Last updated 5 years agofrom:deea44438f. Checks:OK: 1 NOTE: 1. Indexed: yes.

TargetResultDate
Doc / VignettesOKNov 16 2024
R-4.5-linux-x86_64NOTENov 16 2024

Exports:hdbm

Dependencies:RcppRcppArmadillo

High Dimensional Bayesian Mediation Analysis in R

Rendered fromhdbm.Rmdusingknitr::rmarkdownon Nov 16 2024.

Last update: 2019-08-28
Started: 2019-08-28