tag:joss.theoj.org,2005:/papers/tagged/probability%20functionsJournal of Open Source Software2019-02-15T10:05:23ZJournal of Open Source Softwarehttps://joss.theoj.orgtag: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/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 functiontag:joss.theoj.org,2005:Paper/5032018-06-11T10:33:54Z2021-02-15T11:33:21ZPhilentropy: Information Theory and Distance Quantification with Racceptedv0.2.02018-05-23 13:46:00 UTC262018-06-11 10:33:54 UTC32018765Hajk-GeorgDrostThe Sainsbury Laboratory, University of Cambridge, Bateman Street, Cambridge CB2 1LR, UK0000-0002-1567-306X10.21105/joss.00765https://doi.org/10.5281/zenodo.1286221R, C, C++https://joss.theoj.org/papers/10.21105/joss.00765.pdfinformation theory, distance metrics, probability functions, divergence quantification, jensen-shannon divergence