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.
|Author||Xiaogang Su and Razieh Nabi Abdolyousefi|
|Maintainer||Xiaogang Su <[email protected]>|
|Package repository||View on GitHub|
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