https://github.com/JuliaMath/MeasureTheory.jl

"Distributions" that might not add to one.
https://github.com/JuliaMath/MeasureTheory.jl

bayesian-inference julia machine-learning probabilistic-programming probability statistics

Last synced: 5 days ago
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"Distributions" that might not add to one.

• Host: GitHub
• URL: https://github.com/JuliaMath/MeasureTheory.jl
• Owner: JuliaMath
• License: mit
• Created: 2020-01-11T19:44:00.000Z (almost 5 years ago)
• Default Branch: master
• Last Pushed: 2024-05-16T09:48:21.000Z (6 months ago)
• Last Synced: 2024-05-22T03:37:16.682Z (6 months ago)
• Topics: bayesian-inference, julia, machine-learning, probabilistic-programming, probability, statistics
• Language: Julia
• Homepage:
• Size: 4.56 MB
• Stars: 382
• Watchers: 19
• Forks: 31
• Open Issues: 68
• Metadata Files:
  • Readme: README.md
  • Funding: .github/FUNDING.yml
  • License: LICENSE
  • Citation: CITATION.bib

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README

        
# MeasureTheory

[![Stable](https://img.shields.io/badge/docs-stable-blue.svg)](https://JuliaMath.github.io/MeasureTheory.jl/stable)

[![Dev](https://img.shields.io/badge/docs-dev-blue.svg)](https://JuliaMath.github.io/MeasureTheory.jl/dev)

[![Build Status](https://github.com/JuliaMath/MeasureTheory.jl/workflows/CI/badge.svg)](https://github.com/JuliaMath/MeasureTheory.jl/actions)

[![Coverage](https://codecov.io/gh/JuliaMath/MeasureTheory.jl/branch/master/graph/badge.svg)](https://codecov.io/gh/JuliaMath/MeasureTheory.jl)

[![DOI](https://proceedings.juliacon.org/papers/10.21105/jcon.00092/status.svg)](https://doi.org/10.21105/jcon.00092)

`MeasureTheory.jl` is a package for building and reasoning about measures.

## Why?

Probabilistic programming and statistical computing are vibrant areas in the development of the Julia programming language, but the underlying infrastructure dramatically predates recent developments. The goal of MeasureTheory.jl is to provide Julia with the right vocabulary and tools for these tasks. In this package we introduce a well-chosen foundational primitives centered around the notion of measure, density and conditional probability with powerful combinators and transforms intended to power and unify work on probabilistic programming and statistical computing within Julia. Check out our [JuliaCon 2021 article](https://doi.org/10.21105/jcon.00092) detailing our ideas for and with this package.

## Getting started

To install `MeasureTheory.jl`, open the Julia Pkg REPL (by typing `]` in the standard REPL) and run

```julia

pkg> add MeasureTheory

```

To get an idea of the possibilities offered by this package, go to the [documentation](https://JuliaMath.github.io/MeasureTheory.jl/stable).

## Coordination and support

For interaction and shorter usage questions, there is the dedicated channel [#measuretheory on Julia's Zulip chat julialang.zulipchat.com](https://julialang.zulipchat.com/#narrow/stream/259730-measuretheory.2Ejl) and the #measuretheory channel on the [Julia language Slack chat](https://julialang.org/slack/) and for broader discussions [Julia's discourse forum](https://discourse.julialang.org).

Development takes place on Github with [Github's issue ticker](https://github.com/JuliaMath/MeasureTheory.jl/issues) for bug reports and coordination.

We adhere to the [community standards set forward by the Julia community.](https://julialang.org/community/standards/)

## Support

[](https://informativeprior.com/) [](https://planting.space)

## Stargazers over time

[![Stargazers over time](https://starchart.cc/JuliaMath/MeasureTheory.jl.svg)](https://starchart.cc/JuliaMath/MeasureTheory.jl)