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ALassoSurvIC  

Adaptive Lasso for the Cox Regression with Interval Censored and Possibly Left Truncated Data
View on CRAN: Click here


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

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

Install by package version:
library("remotes")
install_version("ALassoSurvIC", "0.1.1")



Attach the package and use:
library("ALassoSurvIC")
Maintained by
Daewoo Pak
[Scholar Profile | Author Map]
First Published: 2019-10-16
Latest Update: 2022-12-01
Description:
Penalized variable selection tools for the Cox proportional hazards model with interval censored and possibly left truncated data. It performs variable selection via penalized nonparametric maximum likelihood estimation with an adaptive lasso penalty. The optimal thresholding parameter can be searched by the package based on the profile Bayesian information criterion (BIC). The asymptotic validity of the methodology is established in Li et al. (2019 ). The unpenalized nonparametric maximum likelihood estimation for interval censored and possibly left truncated data is also available.
How to cite:
Daewoo Pak (2019). ALassoSurvIC: Adaptive Lasso for the Cox Regression with Interval Censored and Possibly Left Truncated Data. R package version 0.1.1, https://cran.r-project.org/web/packages/ALassoSurvIC. Accessed 29 Apr. 2025.
Previous versions and publish date:
0.1.0 (2019-10-16 14:20)
Other packages that cited ALassoSurvIC R package
View ALassoSurvIC citation profile
Other R packages that ALassoSurvIC depends, imports, suggests or enhances
Complete documentation for ALassoSurvIC
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