tag:joss.theoj.org,2005:/papers/tagged/mcmc?page=1Journal of Open Source Software2023-07-26T13:23:53ZJournal of Open Source Softwarehttps://joss.theoj.orgtag:joss.theoj.org,2005:Paper/44502023-07-26T13:23:53Z2023-07-27T00:01:44ZPxMCMC: A Python package for proximal Markov Chain Monte Carloacceptedv0.1.52023-04-24 05:20:17 UTC872023-07-26 13:23:53 UTC820235582AugustinMarignierResearch School of Earth Sciences, Australian National University, Australia0000-0001-6778-139910.21105/joss.05582https://doi.org/10.5281/zenodo.8185139Pythonhttps://joss.theoj.org/papers/10.21105/joss.05582.pdfMCMC, imaging, geophysics, astrophysicstag:joss.theoj.org,2005:Paper/34542022-06-25T19:21:52Z2022-06-26T00:01:14ZMeMC: A package for Monte Carlo simulations of spherical shellsacceptedv1.02022-03-31 12:24:55 UTC742022-06-25 19:21:52 UTC720224305VipinAgrawalNordita, KTH Royal Institute of Technology and Stockholm University, Roslagstullsbacken 23, 10691 Stockholm, Sweden., Department of Physics, Stockholm University, Stockholm, Sweden.0000-0002-1291-5035VikashPandeyNordita, KTH Royal Institute of Technology and Stockholm University, Roslagstullsbacken 23, 10691 Stockholm, Sweden.0000-0002-5120-2142HannaKylhammarKTH Royal Institute of Technology, Sweden.0000-0001-8578-2272ApurbaDevDepartment of Electrical Engineering, The Angstrom Laboratory, Uppsala University, Uppsala, Sweden., Department of Applied Physics, School of Engineering Sciences, KTH Royal Institute of Technology, Stockholm, Sweden.0000-0002-6235-2891DhrubadityaMitraNordita, KTH Royal Institute of Technology and Stockholm University, Roslagstullsbacken 23, 10691 Stockholm, Sweden.0000-0003-4861-815210.21105/joss.04305https://doi.org/10.5281/zenodo.6671531C++, Pythonhttps://joss.theoj.org/papers/10.21105/joss.04305.pdftag:joss.theoj.org,2005:Paper/32932022-04-18T15:53:10Z2022-04-19T00:00:54ZSGMCMCJax: a lightweight JAX library for stochastic gradient Markov chain Monte Carlo algorithmsaccepted0.2.92022-01-17 18:25:10 UTC722022-04-18 15:53:10 UTC720224113JeremieCoullonCervest, London, UK0000-0002-7032-3425ChristopherNemethLancaster University, UK0000-0002-9084-386610.21105/joss.04113https://doi.org/10.5281/zenodo.6460681Pythonhttps://joss.theoj.org/papers/10.21105/joss.04113.pdfJAX, MCMC, SGMCMC, Bayesian inferencetag:joss.theoj.org,2005:Paper/31172022-01-14T14:04:16Z2022-01-15T00:01:27ZcompareMCMCs: An R package for studying MCMC efficiencyaccepted0.5.02021-10-18 20:34:22 UTC692022-01-14 14:04:16 UTC720223844Perryde ValpineUniversity of California, BerkeleySallyPaganinUniversity of California, BerkeleyDanielTurekWilliams College10.21105/joss.03844https://doi.org/10.5281/zenodo.5842623Rhttps://joss.theoj.org/papers/10.21105/joss.03844.pdfstatistics, Markov chain Monte Carlo, nimble, JAGStag:joss.theoj.org,2005:Paper/20472021-05-13T13:24:09Z2021-05-20T20:10:30ZParaMonte: A high-performance serial/parallel Monte Carlo simulation library for C, C++, Fortranacceptedv1.2.02020-09-29 21:20:03 UTC612021-05-13 13:24:09 UTC620212741AmirShahmoradiDepartment of Physics, The University of Texas, Arlington, TX, Data Science Program, The University of Texas, Arlington, TX0000-0002-9720-8937FatemehBagheriDepartment of Physics, The University of Texas, Arlington, TX10.21105/joss.02741https://doi.org/10.5281/zenodo.4749957Python, Fortranhttps://joss.theoj.org/papers/10.21105/joss.02741.pdfC, C++, Monte Carlo, Markov Chain Monte Carlo, Uncertainty Quantification, Metropolis-Hastings, adaptive sampling, MCMC, DRAMtag:joss.theoj.org,2005:Paper/15942020-06-05T20:36:59Z2021-02-15T11:30:51Zuravu: Making Bayesian modelling easy(er)acceptedv0.0.72020-05-20 12:20:56 UTC502020-06-05 20:36:59 UTC520202214AndrewR.McCluskeyDiamond Light Source, Rutherford Appleton Laboratory, Harwell Science and Innovation Campus, Didcot, OX11 0DE, UK, Department of Chemistry, University of Bath, Claverton Down, Bath, BA2 7AY, UK0000-0003-3381-5911TimSnowDiamond Light Source, Rutherford Appleton Laboratory, Harwell Science and Innovation Campus, Didcot, OX11 0DE, UK, School of Chemistry, University of Bristol, Bristol, BS8 1TS, UK0000-0001-7146-688510.21105/joss.02214https://doi.org/10.5281/zenodo.3876888Pythonhttps://joss.theoj.org/papers/10.21105/joss.02214.pdfBayesian, analysis, evidence estimation, nested sampling, mcmctag:joss.theoj.org,2005:Paper/13022019-11-17T18:29:53Z2022-01-18T11:37:45Zemcee v3: A Python ensemble sampling toolkit for affine-invariant MCMCacceptedv3.0.12019-10-28 18:00:31 UTC432019-11-17 18:29:53 UTC420191864DanielForeman-MackeyCenter for Computational Astrophysics, Flatiron Institute0000-0002-9328-5652WillM.FarrCenter for Computational Astrophysics, Flatiron Institute, Department of Physics and Astronomy, Stony Brook University, United States0000-0003-1540-8562ManodeepSinhaCentre for Astrophysics & Supercomputing, Swinburne University of Technology, Australia, ARC Centre of Excellence for All Sky Astrophysics in 3 Dimensions (ASTRO 3D)0000-0002-4845-1228AnneM.ArchibaldUniversity of Newcastle0000-0003-0638-3340DavidW.HoggCenter for Computational Astrophysics, Flatiron Institute, Center for Cosmology and Particle Physics, Department of Physics, New York University0000-0003-2866-9403JeremyS.SandersMax Planck Institute for Extraterrestrial Physics0000-0003-2189-4501JoeZuntzInstitute for Astronomy, University of Edinburgh, Edinburgh, EH9 3HJ, UK0000-0001-9789-9646PeterK. g.WilliamsCenter for Astrophysics | Harvard & Smithsonian, American Astronomical Society0000-0003-3734-3587AndrewR. j.NelsonAustralian Nuclear Science and Technology Organisation, NSW, Australia0000-0002-4548-3558Miguelde Val-BorroPlanetary Science Institute, 1700 East Fort Lowell Rd., Suite 106, Tucson, AZ 85719, USA0000-0002-0455-9384TobiasErhardtClimate and Environmental Physics and Oeschger Center for Climate Change Research, University of Bern, Bern, Switzerland0000-0002-6683-6746IlyaPashchenkoP.N. Lebedev Physical Institute of the Russian Academy of Sciences, Moscow, Russia0000-0002-9404-7023OriolAbrilPlaUniversitat Pompeu Fabra, Barcelona0000-0002-1847-948110.21105/joss.01864https://doi.org/10.5281/zenodo.3543502Pythonhttps://joss.theoj.org/papers/10.21105/joss.01864.pdfastronomytag:joss.theoj.org,2005:Paper/12022019-10-01T17:27:15Z2021-02-15T11:31:40ZBayesPostEst: An R Package to Generate Postestimation Quantities for Bayesian MCMC Estimationaccepted0.1.02019-09-05 18:27:24 UTC422019-10-01 17:27:15 UTC420191722ShanaScoginUniversity of Notre Dame, South Bend, IN, USA0000-0002-7801-853XJohannesKarrethUrsinus College, Collegeville, PA, USA0000-0003-4586-7153AndreasBegerPredictive Heuristics, Bellevue, WA, USA0000-0003-1883-3169RobWilliamsWashington University in St. Louis, St. Louis, MO, USA0000-0001-9259-388310.21105/joss.01722https://doi.org/10.5281/zenodo.3464224Rhttps://joss.theoj.org/papers/10.21105/joss.01722.pdfMCMC, Bayesian methods, Visualization, ROC curves, Precision-Recall curves, Region of Practical Equivalencetag:joss.theoj.org,2005:Paper/11312019-08-12T12:54:20Z2021-02-15T11:31:54Zgreta: simple and scalable statistical modelling in Raccepted0.3.02019-07-26 11:46:05 UTC402019-08-12 12:54:20 UTC420191601NickGoldingSchool of BioSciences, University of Melbourne0000-0001-8916-557010.21105/joss.01601https://doi.org/10.5281/zenodo.819476Rhttps://joss.theoj.org/papers/10.21105/joss.01601.pdfstatistics, statistical modelling, bayesian statistics, mcmc, hamiltonian monte carlo, tensorflowtag:joss.theoj.org,2005:Paper/9752019-07-09T11:38:18Z2021-02-15T11:32:15Zfmcmc: A friendly MCMC frameworkaccepted0.1-02019-04-23 18:15:40 UTC392019-07-09 11:38:18 UTC420191427GeorgeG VegaYonDepartment of Preventive Medicine, University of Southern California0000-0002-3171-0844PaulMarjoramDepartment of Preventive Medicine, University of Southern California0000-0003-0824-744910.21105/joss.01427https://doi.org/10.5281/zenodo.3272759R, C++https://joss.theoj.org/papers/10.21105/joss.01427.pdfmetropolis-hastings, mcmc, markov chain monte carlo, transition kernel, automatic convergence