2021
DOI: 10.18637/jss.v098.i16
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Distributions.jl: Definition and Modeling of Probability Distributions in the JuliaStats Ecosystem

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.

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Cited by 50 publications
(40 citation statements)
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“…6 Used packages in alphabetical order: Agents.jl for agent-based modelling and simulation (Datseris et al, 2021), Colors.jl for coloring of visualisations, CSV.jl for handling delimited files (Quinn et al, 2021), DataFrames.jl for data processing (White et al, 2021), Distributions.jl for probability distributions (Besançon et al, 2021), Latexify.jl for L A T E X-formatting of tables, Makie.jl for visualisations (Danisch et al, 2021), and Pipe.jl for chaining of operations.…”
Section: Simulations and Resultsmentioning
confidence: 99%
“…6 Used packages in alphabetical order: Agents.jl for agent-based modelling and simulation (Datseris et al, 2021), Colors.jl for coloring of visualisations, CSV.jl for handling delimited files (Quinn et al, 2021), DataFrames.jl for data processing (White et al, 2021), Distributions.jl for probability distributions (Besançon et al, 2021), Latexify.jl for L A T E X-formatting of tables, Makie.jl for visualisations (Danisch et al, 2021), and Pipe.jl for chaining of operations.…”
Section: Simulations and Resultsmentioning
confidence: 99%
“…NoisySignalIntegration.jl includes a detailed documentation that covers the typical workflow with several examples. The API uses custom datatypes and convenience functions to aid the data analysis and permits flexible customizations: Any probability distribution from Distributions.jl (Besançon et al, 2021;Lin et al, 2019) is a valid input to express uncertainty in integration bounds, thus allowing to adapt the uncertainty analysis as needed to ones state of knowledge. The core integration function can be swapped if the included trapezoidal integration is deemed unsatisfactory in terms of accuracy.…”
Section: Discussionmentioning
confidence: 99%
“…In the case of signals that promote nearby cells to commit to the opposite lineage, we can follow the same principles to define a signal: These definitions of signaling also allow for multiple cells to signal a single cell at similar times, while still having A 2 well defined. We implemented this model in Julia ( Bezanson et al, 2017 ), where we used the DifferentialEquations.jl ( Rackauckas and Nie, 2017 ) and Distributions.jl ( Besançon et al, 2021 ) packages for numerical simulation.…”
Section: Methodsmentioning
confidence: 99%