tag:joss.theoj.org,2005:/papers/tagged/probabilityJournal 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/26902022-07-20T08:45:55Z2022-07-20T08:45:56ZPyAFBF: a Python library for sampling image textures from the anisotropic fractional Brownian field.acceptedv0.0.22021-05-24 08:46:07 UTC752022-07-20 08:45:55 UTC720223821FrédéricJ.p.RichardAix Marseille University, CNRS, Centrale Marseille, I2M, UMR 7373, Marseille, France.0000-0001-5146-989410.21105/joss.03821https://doi.org/10.5281/zenodo.6860333Pythonhttps://joss.theoj.org/papers/10.21105/joss.03821.pdfmathematics, texture synthesis, image processing, probability, statistics, fractional Brownian fieldtag:joss.theoj.org,2005:Paper/26912021-08-25T13:40:20Z2021-08-26T00:00:44ZSummationByPartsOperators.jl: A Julia library of provably stable discretization techniques with mimetic propertiesacceptedv0.5.12021-05-25 06:00:07 UTC642021-08-25 13:40:20 UTC620213454HendrikRanochaApplied Mathematics Münster, University of Münster, Germany0000-0002-3456-227710.21105/joss.03454https://doi.org/10.5281/zenodo.5226913Julia, Jupyter Notebookhttps://joss.theoj.org/papers/10.21105/joss.03454.pdfnumerical analysis, differential equations, summation-by-parts, energy stability, finite differences, discontinuous Galerkin methods, Fourier collocation methodstag:joss.theoj.org,2005:Paper/27562021-08-11T13:49:00Z2022-01-18T12:05:15ZSurPyval: Survival Analysis with Pythonaccepted0.4.02021-06-13 09:16:35 UTC642021-08-11 13:49:00 UTC620213484DerrynKnifeIndependent researcher10.21105/joss.03484https://doi.org/10.5281/zenodo.5177222Pythonhttps://joss.theoj.org/papers/10.21105/joss.03484.pdfsurvival analysis, parameter estimation, censored data, truncated data, maximum likelihood, product spacing estimation, method of moments, mean square error, probability plotting, probability plotting parameter estimationtag:joss.theoj.org,2005:Paper/13202020-02-05T15:14:48Z2021-02-15T11:31:24Zpasst: An R implementation of the Probability Associator Time (PASS-T) modelacceptedv0.1.02019-11-05 16:03:32 UTC462020-02-05 15:14:48 UTC520201900JohannesTitzDepartment of Psychology, TU Chemnitz, Germany0000-0002-1102-571910.21105/joss.01900https://doi.org/10.5281/zenodo.3638130Rhttps://joss.theoj.org/papers/10.21105/joss.01900.pdfjudgments of frequency, judgments of duration, PASS-T, artificial neural networktag:joss.theoj.org,2005:Paper/10852019-08-13T01:17:59Z2023-10-14T13:24:36ZbayestestR: Describing Effects and their Uncertainty, Existence and Significance within the Bayesian Frameworkacceptedv0.2.32019-06-30 00:45:42 UTC402019-08-13 01:17:59 UTC420191541DominiqueMakowskiNanyang Technological University, Singapore0000-0001-5375-9967MattanS.Ben-ShacharBen-Gurion University of the Negev, Israel0000-0002-4287-4801DanielLüdeckeUniversity Medical Center Hamburg-Eppendorf, Germany0000-0002-8895-320610.21105/joss.01541https://doi.org/10.5281/zenodo.3361605Rhttps://joss.theoj.org/papers/10.21105/joss.01541.pdfBayesian statistics, rstan, eaystats, posterior distribution, Region of practical equivalence, ROPE, probability of direction, Bayes factortag:joss.theoj.org,2005:Paper/8102019-02-15T10:05:23Z2021-02-15T11:32:39ZBoltzMM: an R package for maximum pseudolikelihood estimation of fully-visible Boltzmann machinesaccepted0.1.32019-01-14 07:17:37 UTC342019-02-15 10:05:23 UTC420191193AndrewT.JonesSchool of Mathematics and Physics, University of Queensland, St. Lucia 4072, Queensland AustraliaJessicaJ.BagnallDepartment of Mathematics and Statistics, La Trobe University, Bundoora 3086, Victoria AustraliaHienD.NguyenDepartment of Mathematics and Statistics, La Trobe University, Bundoora 3086, Victoria Australia0000-0002-9958-432X10.21105/joss.01193https://doi.org/10.5281/zenodo.2563411R, C++https://joss.theoj.org/papers/10.21105/joss.01193.pdfartificial neural network, graphical model, maximum pseudolikelihood estimation, multivariate binary data, probability mass functiontag:joss.theoj.org,2005:Paper/4922018-10-27T11:05:52Z2021-02-15T11:33:23ZPyNomaly: Anomaly detection using Local Outlier Probabilities (LoOP).acceptedv0.2.02018-05-08 01:02:08 UTC302018-10-27 11:05:52 UTC32018845ValentinoConstantinouNASA Jet Propulsion Laboratory0000-0002-5279-414310.21105/joss.00845https://doi.org/10.5281/zenodo.1472519Pythonhttps://joss.theoj.org/papers/10.21105/joss.00845.pdfoutlier detection, anomaly detection, probability, nearest neighbors, unsupervised learning, machine learning, statisticstag:joss.theoj.org,2005:Paper/5852018-08-14T23:19:47Z2021-02-15T11:33:07ZCombining a Probability and a Non-Probability Sample in a Capture-Recapture Settingaccepted1.02018-08-06 22:09:49 UTC282018-08-14 23:19:47 UTC32018886BenjaminWilliamsDepartment of Statistical Science, Southern Methodist University0000-0001-8474-506610.21105/joss.00886https://doi.org/10.5281/zenodo.1344665Rhttps://joss.theoj.org/papers/10.21105/joss.00886.pdfnon-probability sampling, combining data sources, capture-recapture samplingtag:joss.theoj.org,2005:Paper/5682018-08-06T14:48:45Z2021-02-15T11:33:10ZlogKDE: log-transformed kernel density estimationacceptedv0.3.12018-07-24 10:43:23 UTC282018-08-06 14:48:45 UTC32018870AndrewT.JonesSchool of Mathematics and Physics, University of Queensland, St. Lucia 4072, Queensland AustraliaHienD.NguyenDepartment of Mathematics and Statistics, La Trobe University, Bundoora 3086, Victoria Australia0000-0002-9958-432XGeoffreyJ.McLachlanSchool of Mathematics and Physics, University of Queensland, St. Lucia 4072, Queensland Australia10.21105/joss.00870https://doi.org/10.5281/zenodo.1339352R, C++https://joss.theoj.org/papers/10.21105/joss.00870.pdfdata visualization, exploratory data analysis, non-parametric, positive data, probability density function