xgsu/coxphMIC: Sparse Estimation of Cox Proportional Hazards Models via Approximated Inforamtion Criterion
Version 0.0.0.9000

This packages computes sparse estimates for Cox PH models via MIC, a short name for "Minimizing approxiamted Inforatmion Criterion". 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 reparameterization step so that it reduces to one unconstrained nonconvex yet smooth programming problem, which can be solved efficiently. Furthermore, the reparameterization tactic yields an additional advantage in terms of circumventing postselection inference.

Getting started

Package details

AuthorXiaogang Su and Razieh Nabi Abdolyousefi
MaintainerXiaogang Su <[email protected]>
LicenseGPL-2
Version0.0.0.9000
Package repositoryView on GitHub
Installation Install the latest version of this package by entering the following in R:
install.packages("devtools")
library(devtools)
install_github("xgsu/coxphMIC")
xgsu/coxphMIC documentation built on May 28, 2017, 7:36 a.m.