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.

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Description file content

Package
compound.Cox
Type
Package
Title
Univariate Feature Selection and Compound Covariate for Predicting Survival
Version
3.13
Date
2018-7-12
Author
Takeshi Emura, Hsuan-Yu Chen, Shigeyuki Matsui, Yi-Hau Chen
Maintainer
Takeshi Emura
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) , statistical methods in Emura et al (2012 PLoS ONE) , Emura & Chen (2016 Stat Methods Med Res) , and Emura et al. (2018-). Algorithms for generating correlated gene expressions are also available.
License
GPL-2
Depends
numDeriv, survival
NeedsCompilation
no
Packaged
2018-07-12 04:04:45 UTC; user
Repository
CRAN
Date/Publication
2018-07-12 04:50:03 UTC

install.packages('compound.Cox')

3.13

4 days ago

Takeshi Emura

GPL-2

Depends on

numDeriv, survival

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