Learn R Programming

HCmodelSets (version 1.1.3)

Regression with a Large Number of Potential Explanatory Variables

Description

Software for performing the reduction, exploratory and model selection phases of the procedure proposed by Cox, D.R. and Battey, H.S. (2017) 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.

Copy Link

Version

Install

install.packages('HCmodelSets')

Monthly Downloads

218

Version

1.1.3

License

GPL-2 | GPL-3

Maintainer

H. Battey

Last Published

March 15th, 2023

Functions in HCmodelSets (1.1.3)

Reduction.Phase

Reduction by successive traversal of hypercubes proposed by Cox, D. R. & Battey, H. S. (2017)
DGP

Data generating process used by Battey, H. S. & Cox, D. R. (2018).
Exploratory.Phase

Perform the Exploratory phase on the hypercube dimension reduction proposed by Cox, D. R. & Battey, H. S. (2017)
LymphomaData

Lymphoma patients data set.
ModelSelection.Phase

Construct sets of well-fitting models as proposed by Cox, D. R. & Battey, H. S. (2017)