Package: bigstep 1.1.2

bigstep: Stepwise Selection for Large Data Sets

Selecting linear and generalized linear models for large data sets using modified stepwise procedure and modern selection criteria (like modifications of Bayesian Information Criterion). Selection can be performed on data which exceed RAM capacity. Bogdan et al., (2004) <doi:10.1534/genetics.103.021683>.

Authors:Piotr Szulc [aut, cre]

bigstep_1.1.2.tar.gz
bigstep_1.1.2.zip(r-4.5)bigstep_1.1.2.zip(r-4.4)bigstep_1.1.2.zip(r-4.3)
bigstep_1.1.2.tgz(r-4.5-any)bigstep_1.1.2.tgz(r-4.4-any)bigstep_1.1.2.tgz(r-4.3-any)
bigstep_1.1.2.tar.gz(r-4.5-noble)bigstep_1.1.2.tar.gz(r-4.4-noble)
bigstep_1.1.2.tgz(r-4.4-emscripten)bigstep_1.1.2.tgz(r-4.3-emscripten)
bigstep.pdf |bigstep.html
bigstep/json (API)
NEWS

# Install 'bigstep' in R:
install.packages('bigstep', repos = c('https://pmszulc.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/pmszulc/bigstep/issues

On CRAN:

Conda:

5.18 score 2 stars 1 packages 51 scripts 432 downloads 17 exports 17 dependencies

Last updated 20 days agofrom:37ab6d4f9c. Checks:9 OK. Indexed: yes.

TargetResultLatest binary
Doc / VignettesOKMar 10 2025
R-4.5-winOKMar 10 2025
R-4.5-macOKMar 10 2025
R-4.5-linuxOKMar 10 2025
R-4.4-winOKMar 10 2025
R-4.4-macOKMar 10 2025
R-4.4-linuxOKMar 10 2025
R-4.3-winOKMar 10 2025
R-4.3-macOKMar 10 2025

Exports:%>%aicattach.big.matrixbackwardbicfast_forwardforwardget_modelmaicmaic2mbicmbic2multi_backwardprepare_dataread.big.matrixreduce_matrixstepwise

Dependencies:BHbiglmbigmemorybigmemory.sriDBIlatticemagrittrMASSMatrixmatrixStatsR.methodsS3R.ooR.utilsRcppRcppEigenspeedglmuuid

The stepwise procedure for big data

Rendered frombigstep.Rmdusingknitr::rmarkdownon Mar 10 2025.

Last update: 2023-05-11
Started: 2018-09-12