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penAFT  

Fit the Regularized Gehan Estimator with Elastic Net and Sparse Group Lasso Penalties
View on CRAN: Click here


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

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

Install by package version:
library("remotes")
install_version("penAFT", "0.3.0")



Attach the package and use:
library("penAFT")
Maintained by
Aaron J. Molstad
[Scholar Profile | Author Map]
First Published: 2022-01-25
Latest Update: 2023-04-18
Description:
The semiparametric accelerated failure time (AFT) model is an attractive alternative to the Cox proportional hazards model. This package provides a suite of functions for fitting one popular estimator of the semiparametric AFT model, the regularized Gehan estimator. Specifically, we provide functions for cross-validation, prediction, coefficient extraction, and visualizing both trace plots and cross-validation curves. For further details, please see Suder, P. M. and Molstad, A. J., (2022+) Scalable algorithms for semiparametric accelerated failure time models in high dimensions, to appear in Statistics in Medicine .
How to cite:
Aaron J. Molstad (2022). penAFT: Fit the Regularized Gehan Estimator with Elastic Net and Sparse Group Lasso Penalties. R package version 0.3.0, https://cran.r-project.org/web/packages/penAFT. Accessed 06 May. 2025.
Previous versions and publish date:
0.2.0 (2022-01-25 09:22)
Other packages that cited penAFT R package
View penAFT citation profile
Other R packages that penAFT depends, imports, suggests or enhances
Complete documentation for penAFT
Functions, R codes and Examples using the penAFT R package
Some associated functions: genSurvData . penAFT-package . penAFT.coef . penAFT.cv . penAFT . penAFT.plot . penAFT.predict . penAFT.trace . 
Some associated R codes: ADMM.ENpath.R . ADMM.SGpath.R . RcppExports.R . genSurvData.R . penAFT.R . penAFT.aux.R . penAFT.cv.R .  Full penAFT package functions and examples
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