Package: compound.Cox
Type: Package
Title: Univariate Feature Selection and Compound Covariate for
        Predicting Survival
Version: 3.30
Date: 2023-07-09
Author: Takeshi Emura, Hsuan-Yu Chen, Shigeyuki Matsui, Yi-Hau Chen
Maintainer: Takeshi Emura <takeshiemura@gmail.com>
Description: 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 (2019)<DOI:10.1016/j.cmpb.2018.10.020>.
 Algorithms for generating correlated gene expressions are also available.
 Estimation of survival functions via copula-graphic (CG) estimators is also implemented, which is useful for
 sensitivity analyses under dependent censoring (Yeh et al 2023) <DOI:10.3390/biomedicines11030797>.
License: GPL-2
Depends: numDeriv, survival, MASS
Encoding: UTF-8
RoxygenNote: 7.2.3
NeedsCompilation: no
Packaged: 2023-07-10 03:33:22 UTC; emura
Repository: CRAN
Date/Publication: 2023-07-10 23:40:23 UTC
Built: R 4.2.0; ; 2023-07-11 04:10:36 UTC; unix
