glmnet: Lasso and Elastic-Net Regularized Generalized Linear Models

Extremely efficient procedures for fitting the entire lasso or elastic-net regularization path for linear regression, logistic and multinomial regression models, Poisson regression and the Cox model. Two recent additions are the multiple-response Gaussian, and the grouped multinomial regression. The algorithm uses cyclical coordinate descent in a path-wise fashion, as described in the paper linked to via the URL below.

Version: 2.0-16
Depends: Matrix (≥ 1.0-6), utils, foreach
Imports: methods
Suggests: survival, knitr, lars
Published: 2018-04-02
Author: Jerome Friedman [aut, cre], Trevor Hastie [aut, cre], Rob Tibshirani [aut, cre], Noah Simon [aut, ctb], Balasubramanian Narasimhan [ctb], Junyang Qian [ctb]
Maintainer: Trevor Hastie <hastie at stanford.edu>
License: GPL-2
URL: http://www.jstatsoft.org/v33/i01/.
NeedsCompilation: yes
Citation: glmnet citation info
Materials: ChangeLog
In views: MachineLearning, Survival
CRAN checks: glmnet results

Downloads:

Reference manual: glmnet.pdf
Vignettes: An Introduction to Glmnet
Fitting the Penalized Cox Model
Package source: glmnet_2.0-16.tar.gz
Windows binaries: r-devel: glmnet_2.0-16.zip, r-release: glmnet_2.0-16.zip, r-oldrel: glmnet_2.0-16.zip
OS X binaries: r-release: glmnet_2.0-16.tgz, r-oldrel: glmnet_2.0-16.tgz
Old sources: glmnet archive

Reverse dependencies:

Reverse depends: AdapEnetClass, bapred, BigTSP, BioMark, CAM, CBPS, cosso, covTest, ctmle, DivMelt, DTRlearn, elasso, EstHer, fcd, glmnetcr, glmtlp, glmvsd, Grace, hdlm, HiCfeat, IGG, InvariantCausalPrediction, ipflasso, lassoscore, Lavash, mcen, mht, MIRL, mmabig, MMMS, MMS, MNS, MultiVarSel, netgsa, parcor, PAS, personalized, PRIMsrc, prototest, qut, refund.wave, regsel, relaxnet, roccv, RVtests, selectiveInference, SIMMS, SparseLearner, SubLasso, TSGSIS, widenet
Reverse imports: anoint, ArCo, aurelius, bastah, BAYESDEF, BeSS, bestglm, blkbox, BootValidation, c060, Causata, CISE, cocoreg, ComICS, CorReg, CovSelHigh, cpt, customizedTraining, DMRnet, dnr, DWLasso, elasticIsing, enetLTS, eNetXplorer, EnsembleBase, EnsemblePenReg, ePCR, episode, eshrink, expandFunctions, FADA, FindIt, fuser, gamreg, gencve, glmnetUtils, GMDH2, graphicalVAR, GWLelast, HDCI, hdi, hdm, hdme, hdnom, HiCblock, HiCglmi, hit, hybridEnsemble, iml, imputeR, IsingFit, kernDeepStackNet, knockoff, LassoSIR, lime, lmmen, lori, LPR, mase, maxnet, mdpeer, MESS, metafuse, MFKnockoffs, mgm, milr, mpath, mplot, mRchmadness, MRFA, msaenet, msr, MWRidge, natural, NCutYX, nnfor, nproc, OHPL, pact, palasso, parboost, partialCI, PDN, pgraph, PhylogeneticEM, politeness, polywog, pre, prioritylasso, rarhsmm, RCPmod, regnet, rminer, RNAseqNet, rolypoly, RPtests, rrpack, RSDA, RTextTools, SentimentAnalysis, sentometrics, SIS, SISIR, slimrec, SOIL, sparsereg, sparsevar, stm, SubgrpID, SurvRank, TANDEM, tsensembler, TVsMiss, XMRF
Reverse suggests: bamlss, BiodiversityR, broom, bWGR, caretEnsemble, catdata, CBDA, ck37r, coefplot, CompareCausalNetworks, EBglmnet, eclust, EHR, emil, ensembleEN, fbRanks, FeatureHashing, flexmix, formulize, FRESA.CAD, fscaret, ggfortify, GWASinlps, heuristica, live, LSAmitR, medflex, mlr, ModelGood, NAM, nscancor, ordinalNet, plotmo, pmml, projpred, pulsar, randomForestSRC, regsem, sAIC, SemiSupervised, simputation, simulator, sparklyr, SPreFuGED, sqlscore, stabs, STPGA, subsemble, SuperLearner, text2vec, varbvs, vimp, vip
Reverse enhances: prediction

Linking:

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