CRAN/E | coxphMIC

coxphMIC

Sparse Estimation of Cox Proportional Hazards Models via Approximated Information Criterion

Installation

About

Sparse estimation for Cox PH models is done via Minimum approximated Information Criterion (MIC) by Su, Wijayasinghe, Fan, and Zhang (2016) doi:10.1111/biom.12484. MIC mimics the best subset selection using a penalized likelihood approach yet with no need of a tuning parameter. The problem is further reformulated with a re-parameterization step so that it reduces to one unconstrained non-convex yet smooth programming problem, which can be solved efficiently. Furthermore, the re-parameterization tactic yields an additional advantage in terms of circumventing post-selection inference.

Key Metrics

Version 0.1.0
R ≥ 3.1.0
Published 2017-04-26 2529 days ago
Needs compilation? no
License GPL-2
CRAN checks coxphMIC results

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Maintainer

Maintainer

Xiaogang Su

xiaogangsu@gmail.com

Authors

Xiaogang Su
Razieh Nabi Abdolyousefi

Material

README
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

Depends

R ≥ 3.1.0
stats ≥ 3.2.5
graphics ≥ 3.2.5
utils ≥3.2.5

Imports

survival ≥ 2.38
numDeriv ≥ 2014.2-1