Package: sgs 0.3.9

Fabio Feser

sgs: Sparse-Group SLOPE: Adaptive Bi-Level Selection with FDR Control

Implementation of Sparse-group SLOPE (SGS) (Feser and Evangelou (2023) <doi:10.48550/arXiv.2305.09467>) models. Linear and logistic regression models are supported, both of which can be fit using k-fold cross-validation. Dense and sparse input matrices are supported. In addition, a general Adaptive Three Operator Splitting (ATOS) (Pedregosa and Gidel (2018) <doi:10.48550/arXiv.1804.02339>) implementation is provided. Group SLOPE (gSLOPE) (Brzyski et al. (2019) <doi:10.1080/01621459.2017.1411269>) and group-based OSCAR models (Feser and Evangelou (2024) <doi:10.48550/arXiv.2405.15357>) are also implemented. All models are available with strong screening rules (Feser and Evangelou (2024) <doi:10.48550/arXiv.2405.15357>) for computational speed-up.

Authors:Fabio Feser [aut, cre]

sgs_0.3.9.tar.gz
sgs_0.3.9.tar.gz(r-4.7-arm64)sgs_0.3.9.tar.gz(r-4.7-x86_64)sgs_0.3.9.tar.gz(r-4.6-arm64)sgs_0.3.9.tar.gz(r-4.6-x86_64)
sgs_0.3.9.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
sgs/json (API)

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

Bug tracker:https://github.com/ff1201/sgs/issues

Uses libs:
  • openblas– Optimized BLAS
  • c++– GNU Standard C++ Library v3
  • openmp– GCC OpenMP (GOMP) support library

On CRAN:

Conda:

openblascppopenmp

3.59 score 1 stars 1 packages 13 scripts 177 downloads 15 exports 81 dependencies

Last updated from:520c238631. Checks:6 OK. Indexed: no.

TargetResultTimeFilesSyslog
linux-devel-arm64OK274
linux-devel-x86_64OK282
source / vignettesOK332
linux-release-arm64OK365
linux-release-x86_64OK251
wasm-releaseOK154

Exports:arma_mvarma_sparseas_sgsatosfit_goscarfit_goscar_cvfit_gslopefit_gslope_cvfit_sgofit_sgo_cvfit_sgsfit_sgs_cvgen_pensgen_toy_datascaled_sgs

Dependencies:BHbigmemorybigmemory.sricaretclasscliclockcodetoolscpp11data.tablediagramdigestdplyre1071farverforeachfuturefuture.applygenericsggplot2globalsgluegowergtablehardhatipredisobanditeratorsKernSmoothlabelinglatticelavalifecyclelistenvlubridatemagrittrMASSMatrixModelMetricsnlmennetnumDerivparallellypillarpkgconfigplyrpROCprodlimprogressrproxypurrrR6RColorBrewerRcppRcppArmadilloRcppEigenrecipesreshape2RlabrlangrpartS7scalesshapeSLOPEsparsevctrsSQUAREMstringistringrsurvivaltibbletidyrtidyselecttimechangetimeDatetzdbutf8uuidvctrsviridisLitewithr

sgs reproducible example

Fabio Feser

Rendered fromreproducible_example.Rmdusingknitr::rmarkdownon May 28 2026.

Last update: 2024-07-15
Started: 2023-05-19