tag:joss.theoj.org,2005:/papers/tagged/linear%20regressionJournal of Open Source Software2023-12-21T11:33:25ZJournal of Open Source Softwarehttps://joss.theoj.orgtag:joss.theoj.org,2005:Paper/46872023-12-21T11:33:25Z2023-12-22T00:00:45Zsparse-lm: Sparse linear regression models in Pythonacceptedv0.5.12023-08-09 17:30:58 UTC922023-12-21 11:33:25 UTC820235867LuisBarroso-LuqueMaterials Sciences Division, Lawrence Berkeley National Laboratory, Berkeley CA, 94720, USA, Department of Materials Science and Engineering, University of California Berkeley, Berkeley CA, 94720, USA0000-0002-6453-9545FengyuXieMaterials Sciences Division, Lawrence Berkeley National Laboratory, Berkeley CA, 94720, USA, Department of Materials Science and Engineering, University of California Berkeley, Berkeley CA, 94720, USA0000-0002-1169-169010.21105/joss.05867https://doi.org/10.5281/zenodo.10246640Pythonhttps://joss.theoj.org/papers/10.21105/joss.05867.pdfscikit-learn, cvxpy, linear regression, regularization, structured sparsitytag:joss.theoj.org,2005:Paper/38312023-02-13T13:30:07Z2023-02-14T00:00:51ZenetLTS: Robust and Sparse Methods for High Dimensional Linear, Binary, and Multinomial Regressionaccepted1.1.02022-08-23 09:31:03 UTC822023-02-13 13:30:07 UTC820234773FatmaSevincKurnazDepartment of Statistics, Yildiz Technical University, Istanbul, Turkey0000-0002-5958-7366PeterFilzmoserInstitute of Statistics and Mathematical Methods in Economics, TU Wien, Vienna, Austria0000-0002-8014-468210.21105/joss.04773https://doi.org/10.5281/zenodo.7598948Rhttps://joss.theoj.org/papers/10.21105/joss.04773.pdfRobust regression, Elastic net, outlier detectiontag:joss.theoj.org,2005:Paper/25512021-07-19T06:13:35Z2021-07-20T00:00:55Zfitgrid: A Python package for multi-channel event-related time series regression modelingacceptedv0.5.02021-04-03 01:04:42 UTC632021-07-19 06:13:35 UTC620213293ThomasP.UrbachDepartment of Cognitive Science, University of California, San Diego0000-0001-7993-142XAndreyS.PortnoyDepartment of Cognitive Science, University of California, San Diego0000-0001-9997-902510.21105/joss.03293https://doi.org/10.5281/zenodo.3581496https://joss.theoj.org/papers/10.21105/joss.03293.pdfPython, EEG electroencephalography, MEG magnetoencephalography, ERP rERP, linear regression, ordinary least squares, linear mixed-effects, exploratory data analysis EDAtag:joss.theoj.org,2005:Paper/25882021-06-06T09:39:04Z2021-06-07T00:01:23Zwbacon: Weighted BACON algorithms for multivariate outlier nomination (detection) and robust linear regressionacceptedv0.32021-04-22 10:04:52 UTC622021-06-06 09:39:04 UTC620213238TobiasSchochUniversity of Applied Sciences and Arts Northwestern Switzerland, School of Business, Riggenbachstrasse 16, CH-4600 Olten, Switzerland0000-0002-1640-339510.21105/joss.03238https://doi.org/10.5281/zenodo.4895167R, Chttps://joss.theoj.org/papers/10.21105/joss.03238.pdfoutlier detection, robustness, survey, linear regression, bounded influencetag:joss.theoj.org,2005:Paper/25352021-04-21T09:33:12Z2021-04-22T00:02:22Zperformance: An R Package for Assessment, Comparison and Testing of Statistical Modelsaccepted0.7.12021-03-23 10:28:04 UTC602021-04-21 09:33:12 UTC620213139DanielLüdeckeUniversity Medical Center Hamburg-Eppendorf, Germany0000-0002-8895-3206MattanS.Ben-ShacharBen-Gurion University of the Negev, Israel0000-0002-4287-4801IndrajeetPatilCenter for Humans and Machines, Max Planck Institute for Human Development, Berlin, Germany0000-0003-1995-6531PhilipWaggonerUniversity of Chicago, USA0000-0002-7825-7573DominiqueMakowskiNanyang Technological University, Singapore0000-0001-5375-996710.21105/joss.03139https://doi.org/10.5281/zenodo.4700887Rhttps://joss.theoj.org/papers/10.21105/joss.03139.pdfeasystats, parameters, regression, linear models, coefficientstag:joss.theoj.org,2005:Paper/22122021-01-05T11:31:37Z2021-02-15T11:29:41ZLinRegOutliers: A Julia package for detecting outliers in linear regressionacceptedv0.8.32020-12-02 18:04:24 UTC572021-01-05 11:31:37 UTC620212892MehmetHakanSatmanDepartment of Econometrics, Istanbul University, Istanbul, Turkey0000-0002-9402-1982ShreeshAdigaDepartment of Electronics and Communication Engineering, RV College of Engineering, Bengaluru, India0000-0002-1818-6961GuillermoAngerisDepartment of Electrical Engineering, Stanford University, Stanford, California, USA0000-0002-4950-3990EmreAkadalDepartment of Informatics, Istanbul University, Istanbul, Turkey0000-0001-6817-012710.21105/joss.02892https://doi.org/10.5281/zenodo.4419418Juliahttps://joss.theoj.org/papers/10.21105/joss.02892.pdflinear regression, outlier detection, robust statisticstag:joss.theoj.org,2005:Paper/21362020-12-23T14:17:27Z2021-02-15T11:29:47Zeffectsize: Estimation of Effect Size Indices and Standardized Parametersaccepted0.4.0.0012020-10-28 16:26:42 UTC562020-12-23 14:17:27 UTC520202815MattanS.Ben-ShacharBen-Gurion University of the Negev, Israel0000-0002-4287-4801DanielLüdeckeUniversity Medical Center Hamburg-Eppendorf, Germany0000-0002-8895-3206DominiqueMakowskiNanyang Technological University, Singapore0000-0001-5375-996710.21105/joss.02815https://doi.org/10.5281/zenodo.4384509Rhttps://joss.theoj.org/papers/10.21105/joss.02815.pdfeasystats, effect size, regression, linear models, standardized coefficientstag:joss.theoj.org,2005:Paper/18482020-10-10T17:18:47Z2021-02-15T11:30:17ZGENRE (GPU Elastic-Net REgression): A CUDA-Accelerated Package for Massively Parallel Linear Regression with Elastic-Net Regularizationacceptedv1.02020-07-10 23:13:10 UTC542020-10-10 17:18:47 UTC520202644ChristopherKhanVanderbilt University0000-0003-3201-3423BrettByramVanderbilt University0000-0003-3693-145910.21105/joss.02644https://doi.org/10.5281/zenodo.4076520Matlab, Cudahttps://joss.theoj.org/papers/10.21105/joss.02644.pdfCUDA, GPU computing, Cyclic coordinate descent, Elastic-net regularization, Linear regressiontag:joss.theoj.org,2005:Paper/18122020-09-09T17:11:18Z2021-02-15T11:30:23ZExtracting, Computing and Exploring the Parameters of Statistical Models using Raccepted0.8.12020-07-01 09:08:04 UTC532020-09-09 17:11:18 UTC520202445DanielLüdeckeUniversity Medical Center Hamburg-Eppendorf, Germany0000-0002-8895-3206MattanS.Ben-ShacharBen-Gurion University of the Negev, Israel0000-0002-4287-4801IndrajeetPatilMax Planck Institute for Human Development, Germany0000-0003-1995-6531DominiqueMakowskiNanyang Technological University, Singapore0000-0001-5375-996710.21105/joss.02445https://doi.org/10.5281/zenodo.4004846R, Rebolhttps://joss.theoj.org/papers/10.21105/joss.02445.pdfeasystats, parameters, regression, linear models, coefficientstag:joss.theoj.org,2005:Paper/14522020-04-27T16:39:17Z2021-02-15T11:31:06Zhypr: An R package for hypothesis-driven contrast codingacceptedv0.1.62020-01-24 09:28:49 UTC482020-04-27 16:39:17 UTC520202134MaximilianM.RabeUniversity of Potsdam0000-0002-2556-5644ShravanVasishthUniversity of Potsdam0000-0003-2027-1994SvenHohensteinUniversity of Potsdam0000-0002-9708-1593ReinholdKlieglUniversity of Potsdam0000-0002-0180-8488DanielJ.SchadUniversity of Potsdam, Tilburg University0000-0003-2586-682310.21105/joss.02134https://doi.org/10.5281/zenodo.3765843Rhttps://joss.theoj.org/papers/10.21105/joss.02134.pdfpsychology, linguistics, linear regression, linear model, statistics, research methods, research hypotheses