HCmodelSets: Regression with a Large Number of Potential Explanatory Variables

Software for performing the reduction, exploratory and model selection phases of the procedure proposed by Cox, D.R. and Battey, H.S. (2017) <doi:10.1073/pnas.1703764114> for sparse regression when the number of potential explanatory variables far exceeds the sample size. The software supports linear regression, likelihood-based fitting of generalized linear regression models and the proportional hazards model fitted by partial likelihood.

Version: 1.1.2
Depends: R (≥ 3.5.0), mvtnorm, ggplot2, survival
Suggests: R.rsp
Published: 2021-06-01
Author: H. H. Hoeltgebaum
Maintainer: H. H. Hoeltgebaum <hh3015 at ic.ac.uk>
BugReports: https://github.com/hhhelfer/HCmodelSets/issues
License: GPL-2 | GPL-3
NeedsCompilation: no
CRAN checks: HCmodelSets results

Documentation:

Reference manual: HCmodelSets.pdf
Vignettes: R packages: vignettes for HCmodelSets

Downloads:

Package source: HCmodelSets_1.1.2.tar.gz
Windows binaries: r-devel: HCmodelSets_1.1.2.zip, r-release: HCmodelSets_1.1.2.zip, r-oldrel: HCmodelSets_1.1.2.zip
macOS binaries: r-release (arm64): HCmodelSets_1.1.2.tgz, r-release (x86_64): HCmodelSets_1.1.2.tgz, r-oldrel: HCmodelSets_1.1.2.tgz
Old sources: HCmodelSets archive

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