Package: quadrupen 1.0-0
quadrupen: Sparse and Group Sparse Linear Models
Fits the solution paths of classical sparse regression models with efficient active set algorithms by solving small sub-problems. Include LASSO, SCAD, MCP, (Sparse) Group-LASSO, Cooperative-LASSO, (Group) LAVA, (Generalized) Fused-Lasso and (Generalized) Elastic-Net. Also provides methods for model selection purpose (information criteria, cross-validation, stability selection).
Authors:
quadrupen_1.0-0.tar.gz
quadrupen_1.0-0.zip(r-4.7)quadrupen_1.0-0.zip(r-4.6)quadrupen_1.0-0.zip(r-4.5)
quadrupen_1.0-0.tgz(r-4.6-x86_64)quadrupen_1.0-0.tgz(r-4.6-arm64)quadrupen_1.0-0.tgz(r-4.5-x86_64)quadrupen_1.0-0.tgz(r-4.5-arm64)
quadrupen_1.0-0.tar.gz(r-4.7-arm64)quadrupen_1.0-0.tar.gz(r-4.7-x86_64)quadrupen_1.0-0.tar.gz(r-4.6-arm64)quadrupen_1.0-0.tar.gz(r-4.6-x86_64)
quadrupen_1.0-0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
quadrupen/json (API)
NEWS
| # Install 'quadrupen' in R: |
| install.packages('quadrupen', repos = c('https://jchiquet.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/jchiquet/quadrupen/issues
Pkgdown/docs site:https://jchiquet.github.io
Last updated from:b1dfd643d7. Checks:13 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel-arm64 | OK | 355 | ||
| linux-devel-x86_64 | OK | 367 | ||
| source / vignettes | OK | 553 | ||
| linux-release-arm64 | OK | 359 | ||
| linux-release-x86_64 | OK | 382 | ||
| macos-release-arm64 | OK | 216 | ||
| macos-release-x86_64 | OK | 608 | ||
| macos-oldrel-arm64 | OK | 271 | ||
| macos-oldrel-x86_64 | OK | 487 | ||
| windows-devel | OK | 423 | ||
| windows-release | OK | 401 | ||
| windows-oldrel | OK | 383 | ||
| wasm-release | OK | 226 |
Exports:bounded_regbounded.regBoundedRegressionFitcoop_lassocriteriacross_validateCrossValidationDataModelelastic_netelastic.netfused_lassoFusedLassoFitgroup_l1linfgroup_lassogroup_lavagroup_sparse_lmGroupLavaFitInformationCriterialassolavaLavaFitmcpQuadrupenFitridgeRidgeRegressionFitscadselectionsparse_coop_lassosparse_group_l1linfsparse_group_lassosparse_lmSparseFitSparseGroupFitstabilityStabilityPath
Dependencies:clicpp11dplyrfarvergenericsggplot2gluegtableisobandlabelinglatticelifecyclemagrittrMatrixpillarpkgconfigpurrrR6RColorBrewerRcppRcppArmadillorlangS7scalesstringistringrtibbletidyrtidyselectutf8vctrsviridisLitewithr
Sparse Group Regression with Quadrupen
Rendered fromgroup-sparse-regression.Rmdusingknitr::rmarkdownon Jun 06 2026.Last update: 2026-06-03
Started: 2026-06-03
LAVA: Recovering Sums of Sparse and Dense Signals
Rendered fromlava.Rmdusingknitr::rmarkdownon Jun 06 2026.Last update: 2026-06-03
Started: 2026-06-03
Sparse Linear Regression with Quadrupen
Rendered fromsparse-regression.Rmdusingknitr::rmarkdownon Jun 06 2026.Last update: 2026-06-03
Started: 2026-06-03
Recovering a Structured Signal with Quadrupen
Rendered fromstructured-signal-recovery.Rmdusingknitr::rmarkdownon Jun 06 2026.Last update: 2026-06-03
Started: 2026-06-03
