Package: swaglm 0.0.1

swaglm: Fast Sparse Wrapper Algorithm for Generalized Linear Models and Testing Procedures for Network of Highly Predictive Variables

Provides a fast implementation of the SWAG algorithm for Generalized Linear Models which allows to perform a meta-learning procedure that combines screening and wrapper methods to find a set of extremely low-dimensional attribute combinations. The package then performs test on the network of selected models to identify the variables that are highly predictive by using entropy-based network measures.

Authors:Lionel Voirol [aut, cre], Yagmur Ozdemir [aut]

swaglm_0.0.1.tar.gz
swaglm_0.0.1.zip(r-4.7-x86_64)swaglm_0.0.1.zip(r-4.7-arm64)swaglm_0.0.1.zip(r-4.6-x86_64)swaglm_0.0.1.zip(r-4.6-arm64)swaglm_0.0.1.zip(r-4.5-x86_64)
swaglm_0.0.1.tgz(r-4.6-x86_64)swaglm_0.0.1.tgz(r-4.6-arm64)swaglm_0.0.1.tgz(r-4.5-x86_64)swaglm_0.0.1.tgz(r-4.5-arm64)
swaglm_0.0.1.tar.gz(r-4.7-arm64)swaglm_0.0.1.tar.gz(r-4.7-x86_64)swaglm_0.0.1.tar.gz(r-4.6-arm64)swaglm_0.0.1.tar.gz(r-4.6-x86_64)
swaglm_0.0.1.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
swaglm/json (API)

# Install 'swaglm' in R:

install.packages('swaglm', repos = c('https://lionelvoirol.r-universe.dev', 'https://cloud.r-project.org'))

Uses libs:

c++– GNU Standard C++ Library v3

On CRAN:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

cpp

2.70 score 217 downloads 3 exports 75 dependencies

Last updated from:3a4e824478. Checks:15 OK. Indexed: yes.

Target	Result	Time
linux-devel-arm64	OK	174
linux-devel-x86_64	OK	216
source / vignettes	OK	297
linux-release-arm64	OK	178
linux-release-x86_64	OK	179
macos-release-arm64	OK	186
macos-release-x86_64	OK	359
macos-oldrel-arm64	OK	151
macos-oldrel-x86_64	OK	423
windows-devel-arm64	OK	270
windows-devel-x86_64	OK	256
windows-release-arm64	OK	281
windows-release-x86_64	OK	217
windows-oldrel-x86_64	OK	192
wasm-release	OK	123

Exports:compute_network swaglm swaglm_test

Dependencies:askpass BH bigmemory bigmemory.sri bit bit64 boot cellranger class cli clipr cpp11 crayon curl data.table DescTools dotCall64 e1071 Exact expm farver fastglm fields forcats Formula fs gdata gld glue gtools haven hms httr igraph jsonlite labeling lattice lifecycle lmom magrittr maps MASS Matrix mime mvtnorm openssl pillar pkgconfig plyr prettyunits progress proxy R6 RColorBrewer Rcpp RcppArmadillo RcppEigen readr readxl rematch rlang rootSolve rstudioapi scales spam sys tibble tidyselect tzdb utf8 uuid vctrs viridisLite vroom withr

Run the SWAG algorithm for generalized linear models

Rendered fromrun_swaglm.Rmdusingknitr::rmarkdown

Last update: 2025-09-18
Started: 2025-09-18

Help page	Topics
compute_network	compute_network
plot.swaglm_network	plot.swaglm_network
predict.swaglm	predict.swaglm
print.swaglm	print.swaglm
print.swaglm_test	print.swaglm_test
summary.swaglm	summary.swaglm
swaglm	swaglm
swaglm_test	swaglm_test

Package: swaglm 0.0.1

swaglm: Fast Sparse Wrapper Algorithm for Generalized Linear Models and Testing Procedures for Network of Highly Predictive Variables

Citation

Readme and manuals

Help Manual

Usage by other packages (reverse dependencies)