Package: bigstep 1.1.1

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_1.1.1.tar.gz
bigstep_1.1.1.zip(r-4.5)bigstep_1.1.1.zip(r-4.4)bigstep_1.1.1.zip(r-4.3)
bigstep_1.1.1.tgz(r-4.4-any)bigstep_1.1.1.tgz(r-4.3-any)
bigstep_1.1.1.tar.gz(r-4.5-noble)bigstep_1.1.1.tar.gz(r-4.4-noble)
bigstep_1.1.1.tgz(r-4.4-emscripten)bigstep_1.1.1.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'))

Peer review:

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

On CRAN:

5.21 score 2 stars 1 packages 54 scripts 365 downloads 17 exports 17 dependencies

Last updated 1 years agofrom:ce6d720602. Checks:OK: 7. Indexed: yes.

TargetResultDate
Doc / VignettesOKNov 01 2024
R-4.5-winOKNov 01 2024
R-4.5-linuxOKNov 01 2024
R-4.4-winOKNov 01 2024
R-4.4-macOKNov 01 2024
R-4.3-winOKNov 01 2024
R-4.3-macOKNov 01 2024

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

Dependencies:BHbiglmbigmemorybigmemory.sriDBIlatticemagrittrMASSMatrixmatrixStatsR.methodsS3R.ooR.utilsRcppRcppEigenspeedglmuuid

The stepwise procedure for big data

Piotr Szulc

Rendered frombigstep.Rmdusingknitr::rmarkdownon Nov 01 2024.

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