Package: HDJM 0.1.0
Jiehuan Sun
HDJM: Penalized High-Dimensional Joint Model
Joint models have been widely used to study the associations between longitudinal biomarkers and a survival outcome. However, existing joint models only consider one or a few longitudinal biomarkers and cannot deal with high-dimensional longitudinal biomarkers. This package can be used to fit our recently developed penalized joint model that can handle high-dimensional longitudinal biomarkers. Specifically, an adaptive lasso penalty is imposed on the parameters for the effects of the longitudinal biomarkers on the survival outcome, which allows for variable selection. Also, our algorithm is computationally efficient, which is based on the Gaussian variational approximation method.
Authors:
HDJM_0.1.0.tar.gz
HDJM_0.1.0.tar.gz(r-4.5-noble)HDJM_0.1.0.tar.gz(r-4.4-noble)
HDJM_0.1.0.tgz(r-4.4-emscripten)HDJM_0.1.0.tgz(r-4.3-emscripten)
HDJM.pdf |HDJM.html✨
HDJM/json (API)
| # Install 'HDJM' in R: |
| install.packages('HDJM', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org')) |
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated 1 years agofrom:e1b19a2607. Checks:OK: 2. Indexed: no.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Dec 04 2024 |
| R-4.5-linux-x86_64 | OK | Dec 04 2024 |
Exports:HDJM_fit
Dependencies:latticeMatrixRcppRcppArmadilloRcppEnsmallenstatmodsurvival
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| control_list | control_list |
| The function to fit penalized HDJM. | HDJM_fit |
| Simulated Longtidunal Data | LongData |
| Simulated Survival Data | SurvData |
