CRAN/E | SelectBoost

SelectBoost

A General Algorithm to Enhance the Performance of Variable Selection Methods in Correlated Datasets

Installation

About

An implementation of the selectboost algorithm (Bertrand et al. 2020, 'Bioinformatics', doi:10.1093/bioinformatics/btaa855), which is a general algorithm that improves the precision of any existing variable selection method. This algorithm is based on highly intensive simulations and takes into account the correlation structure of the data. It can either produce a confidence index for variable selection or it can be used in an experimental design planning perspective.

Citation SelectBoost citation info
fbertran.github.io/SelectBoost/
github.com/fbertran/SelectBoost/
Bug report File report

Key Metrics

Version 2.2.2
R ≥ 2.10
Published 2022-11-30 515 days ago
Needs compilation? no
License GPL-3
CRAN checks SelectBoost results

Downloads

Yesterday 9 -40%
Last 7 days 80 -1%
Last 30 days 267 -7%
Last 90 days 812 -24%
Last 365 days 3.454 +6%

Maintainer

Maintainer

Frederic Bertrand

frederic.bertrand@utt.fr

Authors

Frederic Bertrand

cre / aut

Myriam Maumy-Bertrand

aut

Ismail Aouadi

ctb

Nicolas Jung

ctb

Material

README
NEWS
Reference manual
Package source

Vignettes

Benchmarking the SelectBoost Package for Network Reverse Engineering
Towards Confidence Estimates in Cascade Networks using the SelectBoost Package
Simulation Tools Provided With the Selectboost Package

Classification MSC

62H11
62J12
62J99

macOS

r-release

arm64

r-oldrel

arm64

r-release

x86_64

r-oldrel

x86_64

Windows

r-devel

x86_64

r-release

x86_64

r-oldrel

x86_64

Old Sources

SelectBoost archive

Depends

R ≥ 2.10

Imports

lars
glmnet
igraph
parallel
msgps
Rfast
methods
Cascade
graphics
grDevices
varbvs
spls
abind

Suggests

knitr
markdown
rmarkdown
mixOmics
CascadeData

Reverse Imports

Patterns