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* First steps toward factoring out TransformVariables

* factor out exponential-families and tweedie

* AffinePushfwd <: AbstractPushforward

* don't export `mydot`

* moving things around

* drop TV functionality

* bugfix

* bugfix

* format

* factor out Chain (let's move it to a new package)

* fix type instability

* update Bernoulli

* import massof

* bugfix

* add some methods

* Revert "First steps toward factoring out TransformVariables"

This reverts commit c78c166.

* smfinv => invsmf

* update MeasureBase version

* add some smfs

* edits

* fix typo

* fix laplace

* fix bernoulli

* fix beta

* fix StudentT

* Fix Uniform

* fix Gumbel

* fix Dirichlet

* minor Dirichlet update

* more Dirichlet

* drop as(m::DistributionMeasures.DistributionMeasure) (for now)

* drop tests for Chain

* drop DistributionMeasures dependency (for now)

* fix cauchy

* fixing Binomial

* small updates

* update

* updates

* drop brokwn measures

* fix normal

* asparams methods

* update tests

* smfAD macro

* update tests

* smf(::Normal)

* move import

* add ForwardDiff

* dep constraint

* fix tests

* smf for affine pushfwd

* update tests

* update test name

* tests

* tests

* update StudentT

* tests

* Some `For` updates

* optimize `Normal`

* update insupport for Normal

* update basemeasure for For measures

* some affine updates

* some fixes

* bump version

* formatting

* oops didn't mean to add that

* format

* MeasureBase 0.14 + other updates

* compatibility fixes

* updates

* more fixes

* fixes

* more fixes

* tests passing

* bump version

* drop breakage CI for now

* update Julia versions for CI

* Drop commented-out code
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MeasureTheory

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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 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

pkg> add MeasureTheory

To get an idea of the possibilities offered by this package, go to the documentation.

Coordination and support

For interaction and shorter usage questions, there is the dedicated channel #measuretheory on Julia's Zulip chat julialang.zulipchat.com and the #measuretheory channel on the Julia language Slack chat and for broader discussions Julia's discourse forum.

Development takes place on Github with Github's issue ticker for bug reports and coordination.

We adhere to the community standards set forward by the Julia community.

Support

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