TransHDM
1.0.1High-Dimensional Mediation Analysis via Transfer Learning
Overview
Provides a framework for high-dimensional mediation analysis using transfer learning. The main function TransHDM() integrates large-scale source data to improve the detection power of potential mediators in small-sample target studies. It addresses data heterogeneity via transfer regularization and debiased estimation while controlling the false discovery rate. The package also includes utilities for data generation (gen_simData_homo(), gen_simData_hetero()), baseline methods such as lasso() and dblasso(), sure independence screening via SIS(), and model diagnostics through source_detection(). The methodology is described in Pan et al. (2025) doi:10.1093/bib/bbaf460.
Install
Health
- OK2026-08-0513 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
- NOTE2026-08-0112 OK · 1 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
- OK2026-06-0913 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
- ERROR2026-06-0812 OK · 0 NOTE · 0 WARNING · 1 ERROR · 0 FAILURE
- OK2026-05-0213 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
Show 2 earlier snapshots
- ERROR2026-04-2511 OK · 0 NOTE · 0 WARNING · 1 ERROR · 0 FAILURE
- OK2026-03-185 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
Documentation
- Examples that run
- 71%
- Documented parameters
- 100%
- Return-value docs
- 100%
- References docs
- 8%
Downloads
Repository
Repository practices
Checks run against github.com/gaohuer/transhdm on 2026-08-03.
No development-tooling practices detected in the upstream repository.
Dependencies
Nothing depends on this yet.
Code & Tests
People & History
1 release. R releases are shown for context.
- RR 4.6.0 released · 2026-04-24
- 1.0.1Latest2026-03-18 · current release
- RR 4.5.0 released · 2025-04-11
Package metadata
- First published
- 2026-03-18
- Total releases
- 1 / 1 yrs
- License
- GPL (>= 3) OSI
- Minimum R
- ≥ 4.0.0
- Download size
- not tracked yet
- Installed size
- not tracked yet
- With dependencies
- not tracked yet
Cite
Cite this package
Start here. This is the citation for the package itself.
citation("TransHDM")CRAN DOI
https://doi.org/10.32614/CRAN.package.TransHDMBibTeX, derived from DESCRIPTION
@Manual{TransHDM,
title = {TransHDM: High-Dimensional Mediation Analysis via Transfer Learning},
author = {Gao, Huer and Pan, Lulu and Qin, Guoyou and Yu, Yongfu},
year = {2026},
note = {R package version 1.0.1},
doi = {10.32614/CRAN.package.TransHDM},
url = {https://CRAN.R-project.org/package=TransHDM}
}Derived from the package DESCRIPTION, not from a citation file the authors wrote. If they publish one later, prefer it.
This is the citation for the package. It is not a citation for the R Observatory.
Cite this page
Use this when the claim is about a measurement on this page.
BibTeX
@misc{robservatoryTransHDM,
author = {Balamuta, James Joseph},
title = {{R} {Observatory}: Metrics for {TransHDM} version 1.0.1},
year = {2026},
publisher = {HJJB, LLC},
url = {https://r-observatory.thecoatlessprofessor.com/packages/TransHDM},
note = {Data set. Data release v2026-08-05}
}APA
Balamuta, J. J. (2026). R Observatory: Metrics for TransHDM version 1.0.1 [Data set]. HJJB, LLC. Data release v2026-08-05. https://r-observatory.thecoatlessprofessor.com/packages/TransHDMRIS
TY - DATA
AU - Balamuta, James Joseph
TI - R Observatory: Metrics for TransHDM version 1.0.1
PY - 2026
PB - HJJB, LLC
N1 - Data release v2026-08-05
UR - https://r-observatory.thecoatlessprofessor.com/packages/TransHDM
ER - In prose
These package metrics were obtained from the R Observatory (Balamuta, 2026), data release v2026-08-05, https://r-observatory.thecoatlessprofessor.com/packages/TransHDM.Bound to data release v2026-08-05, which is what makes the numbers on this page reproducible. See how to cite.