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Distributions.jl: Definition and Modeling of Probability Distributions in the JuliaStats Ecosystem

Besançon, Mathieu and Papamarkou, Theodore and Anthoff, David and Arslan, Alex and Byrne, Simon and Lin, Dahua and Pearson, John (2021) Distributions.jl: Definition and Modeling of Probability Distributions in the JuliaStats Ecosystem. Journal of Statistical Software, 98 (16). Art. No. v098i16. ISSN 1548-7660. doi:10.18637/jss.v098.i16. https://resolver.caltech.edu/CaltechAUTHORS:20210915-224515365

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Abstract

Random variables and their distributions are a central part in many areas of statistical methods. The Distributions.jl package provides Julia users and developers tools for working with probability distributions, leveraging Julia features for their intuitive and flexible manipulation, while remaining highly efficient through zero-cost abstractions.


Item Type:Article
Related URLs:
URLURL TypeDescription
https://doi.org/10.18637/jss.v098.i16DOIArticle
https://arxiv.org/abs/1907.08611arXivDiscussion Paper
ORCID:
AuthorORCID
Besançon, Mathieu0000-0002-6284-3033
Papamarkou, Theodore0000-0002-9689-543X
Anthoff, David0000-0001-9319-2109
Byrne, Simon0000-0001-8048-6810
Lin, Dahua0000-0002-8865-7896
Pearson, John0000-0002-9876-7837
Additional Information:This work is licensed under the licenses Paper: Creative Commons Attribution 3.0 Unported License Code: GNU General Public License (at least one of version 2 or version 3) or a GPL-compatible license. Published by the Foundation for Open Access Statistics. Submitted: 2019-03-19; Accepted: 2020-11-15. Published: 2021-07-25. The authors thank and acknowledge the work of all contributors and maintainers of packages of the JuliaStats ecosystem and especially Dave Kleinschmidt for his valuable feedback on early versions of this article, Andreas Noack for the overall supervision of the package, including the integration of numerous pull requests from external contributors, Moritz Schauer for discussions on the representability of mathematical objects in the Julia type system and Zenna Tavares for the critical review of early drafts. Research sponsored by the Laboratory Directed Research and Development Program of Oak Ridge National Laboratory, managed by UT-Battelle, LLC, for the US Department of Energy under contract DE-AC05-00OR22725. This research used resources of the Compute and Data Environment for Science (CADES) at the Oak Ridge National Laboratory, which is supported by the Office of Science of the U.S. Department of Energy under Contract No. DE-AC05-00OR22725. This applies specifically to funding provided by the Oak Ridge National Laboratory to Theodore Papamarkou.
Funders:
Funding AgencyGrant Number
Department of Energy (DOE)DE-AC05-00OR22725
Subject Keywords:Julia, distributions, modeling, interface, mixture, KDE, sampling, probabilistic programming, inference
Issue or Number:16
DOI:10.18637/jss.v098.i16
Record Number:CaltechAUTHORS:20210915-224515365
Persistent URL:https://resolver.caltech.edu/CaltechAUTHORS:20210915-224515365
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:110913
Collection:CaltechAUTHORS
Deposited By: Tony Diaz
Deposited On:16 Sep 2021 17:11
Last Modified:16 Sep 2021 17:11

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