tag:joss.theoj.org,2005:/papers/tagged/categorical%20dataJournal of Open Source Software2021-10-27T15:43:41ZJournal of Open Source Softwarehttps://joss.theoj.orgtag:joss.theoj.org,2005:Paper/29962021-10-27T15:43:41Z2021-10-28T00:06:22Zserp: An R package for smoothing in ordinal regressionacceptedv.0.2.02021-08-25 06:55:39 UTC662021-10-27 15:43:41 UTC620213705EjikeR.UgbaDepartment of Mathematics and Statistics, School of Economics and Social Sciences, Helmut Schmidt University, Hamburg, Germany0000-0003-2572-002310.21105/joss.03705https://doi.org/10.5281/zenodo.5596864Rhttps://joss.theoj.org/papers/10.21105/joss.03705.pdfregularization, identification problem, cumulative models, categorical data, proportional odds, shrinkage penaltytag:joss.theoj.org,2005:Paper/13922020-05-21T01:16:32Z2021-02-15T11:31:17Zggalluvial: Layered Grammar for Alluvial Plotsacceptedv0.11.12019-12-05 18:54:40 UTC492020-05-21 01:16:32 UTC520202017JasonCoryBrunsonCenter for Quantitative Medicine, UConn Health0000-0003-3126-949410.21105/joss.02017https://doi.org/10.5281/zenodo.3836748Rhttps://joss.theoj.org/papers/10.21105/joss.02017.pdfggplot2, alluvial plots, statistical graphics, data visualization, repeated measures data, categorical datatag:joss.theoj.org,2005:Paper/12712019-12-08T12:11:31Z2021-02-15T11:31:33Zperccalc: An R package for estimating percentiles from categorical variablesacceptedv1.0.42019-10-03 12:52:32 UTC442019-12-08 12:11:31 UTC420191796JorgeCimentadaLaboratory of Digital and Computational Demography, Max Planck Institute of Demographic Research (MPIDR)0000-0001-5594-115610.21105/joss.01796https://doi.org/10.5281/zenodo.3559855Rhttps://joss.theoj.org/papers/10.21105/joss.01796.pdfcategorical data analysis, achievement gapstag:joss.theoj.org,2005:Paper/3252018-01-22T18:08:24Z2021-02-15T11:33:46ZCategory Encoders: a scikit-learn-contrib package of transformers for encoding categorical dataacceptedv1.2.52017-12-05 21:28:08 UTC212018-01-22 18:08:24 UTC32018501WilliamD.McGinnisPredikto, Inc., Helton Tech, LLC0000-0002-3009-9465ChapmanSiuSuncorp Group Ltd.0000-0002-2089-3796AndreSJungle AI0000-0001-5104-0465HanyuHuangTencent, Inc.0000-0001-8503-101410.21105/joss.00501https://doi.org/10.5281/zenodo.1157110Pythonhttps://joss.theoj.org/papers/10.21105/joss.00501.pdfmachine learning, python, sckit-learn