tag:joss.theoj.org,2005:/papers/tagged/GLMMJournal of Open Source Software2023-02-21T15:19:54ZJournal of Open Source Softwarehttps://joss.theoj.orgtag:joss.theoj.org,2005:Paper/36532023-02-21T15:19:54Z2023-02-22T00:00:52ZdsBinVal: Conducting distributed ROC analysis using DataSHIELDacceptedv1.0.12022-06-13 12:52:25 UTC822023-02-21 15:19:54 UTC820234545DanielSchalkDepartment of Statistics, LMU Munich, Munich, Germany, DIFUTURE (DataIntegration for Future Medicine, www.difuture.de), LMU Munich, Munich, Germany, Munich Center for Machine Learning, Munich, Germany0000-0003-0950-1947VerenaSophiaHoffmannInstitute for Medical Information Processing, Biometry and Epidemiology, LMU Munich, Munich, Germany, DIFUTURE (DataIntegration for Future Medicine, www.difuture.de), LMU Munich, Munich, GermanyBerndBischlDepartment of Statistics, LMU Munich, Munich, Germany, Munich Center for Machine Learning, Munich, GermanyUlrichMansmannInstitute for Medical Information Processing, Biometry and Epidemiology, LMU Munich, Munich, Germany, DIFUTURE (DataIntegration for Future Medicine, www.difuture.de), LMU Munich, Munich, Germany10.21105/joss.04545https://doi.org/10.5281/zenodo.7634619Rhttps://joss.theoj.org/papers/10.21105/joss.04545.pdfDataSHIELD, distributed computing, distributed analysis, privacy-preserving, diagnostic tests, prognostic model, model validation, ROC-GLM, discrimination, calibration, Brier scoretag:joss.theoj.org,2005:Paper/19082022-02-14T13:53:07Z2022-02-15T00:01:06ZgLBM: A GPU enabled Lattice Boltzmann Method Libraryacceptedv1.0.02020-07-24 12:52:58 UTC702022-02-14 13:53:07 UTC720222555AaronBrayKitware, Inc., Carrboro, NC 275100000-0002-2188-7646RachelB.ClippKitware, Inc., Carrboro, NC 275100000-0001-6077-978XM.UmarQureshiKitware, Inc., Carrboro, NC 27510SorinMitranDepartment of Mathematics, University of North Carolina, Chapel Hill, NC 27599-32500000-0003-4518-0116AndinetEnquobahrieKitware, Inc., Carrboro, NC 2751010.21105/joss.02555https://doi.org/10.5281/zenodo.6076998C++, Cudahttps://joss.theoj.org/papers/10.21105/joss.02555.pdfGPU, Lattice Boltzmann Method, Computational Fluid Dynamicstag: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/6222018-10-31T19:00:00Z2021-02-15T11:33:00Zrr2: An R package to calculate $R^2$s for regression modelsacceptedv1.0.02018-09-14 17:13:45 UTC302018-10-31 19:00:00 UTC320181028AnthonyR.IvesDepartment of Integrative Biology, UW-Madison, Madison, WI 537060000-0001-9375-9523DaijiangLiDepartment of Wildlife Ecology and Conservation, University of Florida, Gainesville, FL 326110000-0002-0925-342110.21105/joss.01028https://doi.org/10.5281/zenodo.1475416Rhttps://joss.theoj.org/papers/10.21105/joss.01028.pdf$R^2$, GLMM, phylogenetic regression, models with correlated datatag:joss.theoj.org,2005:Paper/6152018-09-20T17:38:43Z2021-02-15T11:33:02Zungroup: An R package for efficient estimation of smooth distributions from coarsely binned dataacceptedv1.0.32018-09-10 12:57:29 UTC292018-09-20 17:38:43 UTC32018937MariusD.PascariuInstitute of Public Health, Center on Population Dynamics, University of Southern Denmark, Odense, Denmark0000-0002-2568-6489MaciejJ.DańkoMax Planck Institute for Demographic Research, Rostock, Germany0000-0002-7924-9022JonasSchöleyInstitute of Public Health, Center on Population Dynamics, University of Southern Denmark, Odense, Denmark0000-0002-3340-8518SilviaRizziInstitute of Public Health, Unit of Epidemiology Biostatistics and Biodemography, University of Southern Denmark, Odense, Denmark10.21105/joss.00937https://doi.org/10.5281/zenodo.1421648R, C++https://joss.theoj.org/papers/10.21105/joss.00937.pdfcomposite link model, GLM, histogram, binned data, smoothing