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r / packages / r-coxphmic

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.

Type Size Name Uploaded Downloads Labels
conda 61.2 kB | noarch/r-coxphmic-0.1.0-r43h142f84f_0.tar.bz2  1 year and 5 months ago 49 main
conda 60.8 kB | noarch/r-coxphmic-0.1.0-r42h142f84f_0.tar.bz2  3 years and 7 days ago 61 main
conda 65.7 kB | noarch/r-coxphmic-0.1.0-r36h6115d3f_0.tar.bz2  5 years and 3 months ago 130 main

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