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:Julien Chiquet [aut, cre]

quadrupen_1.0-0.tar.gz
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quadrupen_1.0-0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
quadrupen/json (API)

# 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

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

On CRAN:

Conda:

openblascppopenmp

6.46 score 1 stars 76 scripts 663 downloads 1 mentions 35 exports 33 dependencies

Last updated from:b1dfd643d7. Checks:13 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-arm64OK379
linux-devel-x86_64OK384
source / vignettesOK589
linux-release-arm64OK384
linux-release-x86_64OK410
macos-release-arm64OK268
macos-release-x86_64OK696
macos-oldrel-arm64OK334
macos-oldrel-x86_64OK646
windows-develOK496
windows-releaseOK507
windows-oldrelOK398
wasm-releaseOK288

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
Setup | Fitting group-sparse linear models | Group Lasso | Cooperative Lasso | Sparse Group Lasso | Fit objects | Regularization paths | Information criteria | Model extraction | Cross-validation | Cross-validation on $\lambda_1 \times \lambda_2$ | Prediction | Stability selection | Debiased Estimator
Rendered fromgroup-sparse-regression.Rmdusingknitr::rmarkdown

Last update: 2026-06-03
Started: 2026-06-03

LAVA: Recovering Sums of Sparse and Dense Signals
Motivation | Setup | Simulation: a mixed sparse + dense signal | Fitting with lava() | Regularization paths by component | Model Selection | Model extraction and decomposition | Comparing estimators | Cross-validation | Group LAVA: group-sparse + dense decomposition | Simulation with a group-sparse signal | Fitting | Paths of the sparse and dense components | Model selection | Group identification | Reference
Rendered fromlava.Rmdusingknitr::rmarkdown

Last update: 2026-06-03
Started: 2026-06-03

Sparse Linear Regression with Quadrupen
Setup | Fitting sparse linear models | Lasso | SCAD | MCP | Elastic-Net | Fit objects | Regularization paths | Information criteria | Model extraction | Cross-validation | Cross-validation on $\lambda_1 \times \lambda_2$ | Prediction | Stability selection | Debiased Estimators
Rendered fromsparse-regression.Rmdusingknitr::rmarkdown

Last update: 2026-06-03
Started: 2026-06-03

Recovering a Structured Signal with Quadrupen
Motivation | Setup | Simulation | Community graph and its Laplacian | Lasso: a baseline without structural knowledge | Fused Lasso: penalizing differences between consecutive predictors | Fused Lasso with the community graph | Structured Ridge: shrinking toward block-constant solutions | Standard ridge | Structured ridge ($S = L_2$) | Structured Elastic-net: sparsity + graph-Laplacian regularization | Debiased structured Elastic-net | Coefficient recovery: a side-by-side comparison
Rendered fromstructured-signal-recovery.Rmdusingknitr::rmarkdown

Last update: 2026-06-03
Started: 2026-06-03

Readme and manuals

Help Manual

Help pageTopics
Fit a linear model with infinity-norm plus ridge-like regularizationbounded.reg bounded_reg
Class "BoundedRegression"BoundedRegressionFit
Extract model coefficientscoef.QuadrupenFit
Penalized criteria based on estimation of degrees of freedomcriteria criteria.QuadrupenFit
Cross-validation for Quadrupen objectcross_validate cross_validate.QuadrupenFit
Class CrossValidationCrossValidation
Data ClassDataModel
Extract model deviancedeviance.QuadrupenFit
Extracts model fitted valuesfitted.QuadrupenFit
A function for fitting generalized fused-Lasso problemsfused_lasso
Class "FusedLassoFit"FusedLassoFit
Fit a linear model with group-lava regularizationgroup_lava
Fit a linear model with (sparse) group regularisationcoop_lasso group_l1linf group_lasso group_sparse_lm sparse_coop_lasso sparse_group_l1linf sparse_group_lasso
Class "GroupLavaFit"GroupLavaFit
Class InformationCriteriaInformationCriteria
Auxiliary functions to check the given class of an objectisQuadrupenFit
Fit a linear model with lava regularizationlava
Class "LavaFit"LavaFit
Plot method for quadrupen objectsplot.CrossValidation plot.QuadrupenFit plot.StabilityPath
Perform model predictionpredict.QuadrupenFit
Class "QuadrupenFit"QuadrupenFit
Extract model residualsresiduals.QuadrupenFit
Fit a linear model with a structured ridge regularizationridge
Class "RidgeRegressionFit"RidgeRegressionFit
Variable selection from a stability pathselection selection.StabilityPath
Fit a linear model with sparse regularizationelastic.net elastic_net lasso mcp scad sparse_lm
Class "SparseFit"SparseFit
Class "SparseGroupFit"SparseGroupFit
Stability selection for Quadrupen objectstability stability.QuadrupenFit
Class StabilityPathStabilityPath