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: 1.1.1
Depends: R (≥ 3.5.0), mvtnorm, ggplot2, survival
Suggests: R.rsp
Published: 2020-04-20
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


Reference manual: HCmodelSets.pdf
Vignettes: R packages: vignettes for HCmodelSets
Package source: HCmodelSets_1.1.1.tar.gz
Windows binaries: r-devel: HCmodelSets_1.1.1.zip, r-release: HCmodelSets_1.1.1.zip, r-oldrel: HCmodelSets_1.1.1.zip
macOS binaries: r-release: HCmodelSets_1.1.1.tgz, r-oldrel: HCmodelSets_1.1.1.tgz
Old sources: HCmodelSets archive

Reverse dependencies:

Reverse suggests: BeSS, bestridge


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