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HDJM  

Penalized High-Dimensional Joint Model
View on CRAN: Click here


Download and install HDJM package within the R console
Install from CRAN:
install.packages("HDJM")

Install from Github:
library("remotes")
install_github("cran/HDJM")

Install by package version:
library("remotes")
install_version("HDJM", "0.1.0")



Attach the package and use:
library("HDJM")
Maintained by
Jiehuan Sun
[Scholar Profile | Author Map]
First Published: 2023-09-02
Latest Update: 2023-09-02
Description:
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.
How to cite:
Jiehuan Sun (2023). HDJM: Penalized High-Dimensional Joint Model. R package version 0.1.0, https://cran.r-project.org/web/packages/HDJM. Accessed 03 May. 2025.
Previous versions and publish date:
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Complete documentation for HDJM
Functions, R codes and Examples using the HDJM R package
Full HDJM package functions and examples
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