tag:joss.theoj.org,2005:/papers/tagged/LassoJournal of Open Source Software2022-09-23T14:45:34ZJournal of Open Source Softwarehttps://joss.theoj.orgtag:joss.theoj.org,2005:Paper/36132022-09-23T14:45:34Z2022-09-25T16:58:01Zhaldensify: Highly adaptive lasso conditional density estimation in Racceptedv0.2.52022-05-18 15:31:04 UTC772022-09-23 14:45:34 UTC720224522NimaS.HejaziDepartment of Biostatistics, T.H. Chan School of Public Health, Harvard University0000-0002-7127-2789MarkJ.van der LaanDivision of Biostatistics, School of Public Health, University of California, Berkeley, Department of Statistics, University of California, Berkeley0000-0002-1019-8343DavidBenkeserDepartment of Biostatistics and Bioinformatics, Rollins School of Public Health, Emory University0000-0002-1019-834310.21105/joss.04522https://doi.org/10.5281/zenodo.7089147Rhttps://joss.theoj.org/papers/10.21105/joss.04522.pdfmachine learning, causal inference, conditional density estimation, generalized propensity score, inverse probability weighting, semiparametric inferencetag:joss.theoj.org,2005:Paper/31162021-12-10T15:24:09Z2021-12-11T00:01:44ZGGLasso - a Python package for General Graphical Lasso computationacceptedv0.1.42021-10-18 16:15:11 UTC682021-12-10 15:24:09 UTC620213865FabianSchaippTechnische Universität München0000-0002-0673-9944OlegVlasovetsInstitute of Computational Biology, Helmholtz Zentrum München, Department of Statistics, Ludwig-Maximilians-Universität MünchenChristianL.MüllerInstitute of Computational Biology, Helmholtz Zentrum München, Department of Statistics, Ludwig-Maximilians-Universität München, Center for Computational Mathematics, Flatiron Institute, New York0000-0002-3821-708310.21105/joss.03865https://doi.org/10.5281/zenodo.5718440Jupyter Notebook, Pythonhttps://joss.theoj.org/papers/10.21105/joss.03865.pdfgraphical lasso, latent graphical model, structured sparsity, convex optimization, ADMMtag:joss.theoj.org,2005:Paper/31092021-12-06T09:55:07Z2021-12-07T00:01:16ZordPens: An R package for Selection, Smoothing and Principal Components Analysis for Ordinal Variablesaccepted1.0.02021-10-12 11:20:51 UTC682021-12-06 09:55:07 UTC620213828AisoudaHoshiyarSchool of Economics and Social Sciences, Helmut Schmidt University, Hamburg, Germany0000-0002-5702-130X10.21105/joss.03828https://doi.org/10.5281/zenodo.5718572Rhttps://joss.theoj.org/papers/10.21105/joss.03828.pdfsmoothing, ordinal ANOVA, Nonlinear Principal Components Analysis, fusion, lassotag:joss.theoj.org,2005:Paper/23652021-02-24T17:21:47Z2021-02-25T00:01:38ZGroupyr: Sparse Group Lasso in Pythonacceptedv0.2.02021-02-01 13:31:54 UTC582021-02-24 17:21:47 UTC620213024AdamRichie-HalfordeScience Institute, University of Washington0000-0001-9276-9084ManjariNarayanDepartment of Psychiatry and Behavioral Sciences, Stanford University0000-0001-5348-270XNoahSimonDepartment of Biostatistics, University of Washington0000-0002-8985-2474JasonYeatmanGraduate School of Education and Division of Developmental and Behavioral Pediatrics, Stanford University0000-0002-2686-1293ArielRokemDepartment of Psychology, University of Washington0000-0003-0679-198510.21105/joss.03024https://doi.org/10.5281/zenodo.4559599Pythonhttps://joss.theoj.org/papers/10.21105/joss.03024.pdfgroup lasso, penalized regression, classificationtag:joss.theoj.org,2005:Paper/21442021-01-17T09:12:07Z2021-02-15T11:29:46Zc-lasso - a Python package for constrained sparse and robust regression and classificationacceptedv1.02020-11-02 09:36:34 UTC572021-01-17 09:12:07 UTC620212844LéoSimpsonTechnische Universität MünchenPatrickL.CombettesDepartment of Mathematics, North Carolina State University, RaleighChristianL.MüllerCenter for Computational Mathematics, Flatiron Institute, New York, Institute of Computational Biology, Helmholtz Zentrum München, Department of Statistics, Ludwig-Maximilians-Universität München0000-0002-3821-708310.21105/joss.02844https://doi.org/10.6084/m9.figshare.13589585.v1Python, JavaScripthttps://joss.theoj.org/papers/10.21105/joss.02844.pdfregression, classification, constrained regression, Lasso, Huber function, Square Hinge SVM, convex optimization, perspective functiontag:joss.theoj.org,2005:Paper/17942020-09-26T07:36:15Z2021-02-15T11:30:26Zhal9001: Scalable highly adaptive lasso regression in Racceptedv0.2.62020-06-24 02:07:17 UTC532020-09-26 07:36:15 UTC520202526NimaS.HejaziGraduate Group in Biostatistics, University of California, Berkeley, Division of Biostatistics, School of Public Health, University of California, Berkeley, Center for Computational Biology, University of California, Berkeley0000-0002-7127-2789JeremyR.CoyleDivision of Biostatistics, School of Public Health, University of California, Berkeley0000-0002-9874-6649MarkJ.van der LaanDivision of Biostatistics, School of Public Health, University of California, Berkeley, Department of Statistics, University of California, Berkeley, Center for Computational Biology, University of California, Berkeley0000-0003-1432-551110.21105/joss.02526https://doi.org/10.5281/zenodo.4050561R, C++https://joss.theoj.org/papers/10.21105/joss.02526.pdfmachine learning, targeted learning, causal inferencetag:joss.theoj.org,2005:Paper/13792020-03-01T23:43:39Z2021-02-15T11:31:19ZPyglmnet: Python implementation of elastic-net regularized generalized linear modelsacceptedv1.12019-11-26 03:54:41 UTC472020-03-01 23:43:39 UTC520201959MainakJasMassachusetts General Hospital, Harvard Medical School0000-0002-3199-9027TitipatAchakulvisutUniversity of Pennsylvania0000-0002-2124-2979AidIdrizovićLoyola UniversityDanielAcunaUniversity of SyracuseMatthewAntalekNorthwestern UniversityViniciusMarquesLoyola UniversityTommyOdlandSonat ConsultingRaviPrakashGargNorthwestern UniversityMayankAgrawalPrinceton UniversityYuUmegakiNTT DATA Mathematical Systems IncPeterFoley6050000-0002-0304-7213HugoFernandesRockets of Awesome0000-0002-0168-4104DrewHarrisEpoch CapitalBeibinLiUniversity of WashingtonOlivierPietersIDLab-AIRO -- Ghent University -- imec, Research Institute for Agriculture, Fisheries and Food0000-0002-5473-4849ScottOttersonClean Power ResearchGiovanniDe ToniUniversity of Trento0000-0002-8387-9983ChrisRodgersColumbia University0000-0003-1762-3450EvaDyerGeorgia TechMattiHamalainenMassachusetts General Hospital, Harvard Medical SchoolKonradKordingUniversity of PennsylvaniaPavanRamkumarSystem1 Biosciences Inc0000-0001-7450-072710.21105/joss.01959https://doi.org/10.5281/zenodo.3686564Pythonhttps://joss.theoj.org/papers/10.21105/joss.01959.pdfglm, machine-learning, lasso, elastic-net, group-lassotag:joss.theoj.org,2005:Paper/12072019-12-06T05:25:08Z2021-02-15T11:31:39Zxrnet: Hierarchical Regularized Regression to Incorporate External Dataaccepted0.0.0.90002019-09-08 03:21:23 UTC442019-12-06 05:25:08 UTC420191761GarrettM.WeaverDepartment of Preventive Medicine, University of Southern California0000-0002-9918-8386JuanPabloLewingerDepartment of Preventive Medicine, University of Southern California10.21105/joss.01761https://doi.org/10.5281/zenodo.3564788R, C++https://joss.theoj.org/papers/10.21105/joss.01761.pdfregularized regression, lasso regression, ridge regression, elastic net regression, hierarchical regressiontag:joss.theoj.org,2005:Paper/222016-07-01T00:00:00Z2021-02-15T11:34:32ZPrism: Multiple spline regression with regularization, dimensionality reduction, and feature selectionacceptedv2.0.02016-06-23 17:31:27 UTC32016-07-01 00:00:00 UTC1201631ChristopherR.MadanBoston College0000-0003-3228-650110.21105/joss.00031https://doi.org/10.5281/zenodo.56821Matlabhttps://joss.theoj.org/papers/10.21105/joss.00031.pdfregression, smoothing spline, matlab, pca, relevance vector machine, multiple regression, lasso