CRAN/E | ALassoSurvIC

ALassoSurvIC

Adaptive Lasso for the Cox Regression with Interval Censored and Possibly Left Truncated Data

Installation

About

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 doi:10.1177/0962280219856238). The unpenalized nonparametric maximum likelihood estimation for interval censored and possibly left truncated data is also available.

Key Metrics

Version 0.1.1
R ≥ 3.5.0
Published 2022-12-01 484 days ago
Needs compilation? yes
License GPL (≥ 3)
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Maintainer

Maintainer

Daewoo Pak

heavyrain.pak@gmail.com

Authors

Chenxi Li
Daewoo Pak
David Todem

Material

README
NEWS
Reference manual
Package source

macOS

r-release

arm64

r-oldrel

arm64

r-release

x86_64

r-oldrel

x86_64

Windows

r-devel

x86_64

r-release

x86_64

r-oldrel

x86_64

Old Sources

ALassoSurvIC archive

Depends

R ≥ 3.5.0

Imports

Rcpp
parallel

LinkingTo

Rcpp