compound.Cox: Univariate Feature Selection and Compound Covariate for Predicting Survival

Univariate feature selection and compound covariate methods under the Cox model with high-dimensional features (e.g., gene expressions). Available are survival data for non-small-cell lung cancer patients with gene expressions (Chen et al 2007 New Engl J Med) <doi:10.1056/NEJMoa060096>, statistical methods in Emura et al (2012 PLoS ONE) <doi:10.1371/journal.pone.0047627>, Emura & Chen (2016 Stat Methods Med Res) <doi:10.1177/0962280214533378>, and Emura et al. (2018-)<submitted>. Algorithms for generating correlated gene expressions are also available.

Version: 3.13
Depends: numDeriv, survival
Published: 2018-07-12
Author: Takeshi Emura, Hsuan-Yu Chen, Shigeyuki Matsui, Yi-Hau Chen
Maintainer: Takeshi Emura <takeshiemura at gmail.com>
License: GPL-2
NeedsCompilation: no
In views: Survival
CRAN checks: compound.Cox results

Downloads:

Reference manual: compound.Cox.pdf
Package source: compound.Cox_3.13.tar.gz
Windows binaries: r-devel: compound.Cox_3.13.zip, r-release: compound.Cox_3.13.zip, r-oldrel: compound.Cox_3.13.zip
OS X binaries: r-release: compound.Cox_3.13.tgz, r-oldrel: compound.Cox_3.13.tgz
Old sources: compound.Cox archive

Reverse dependencies:

Reverse depends: Bivariate.Pareto, GFGM.copula

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