# \[ANN\] ABCdeZ.jl -- Bayesian inference / model evidences

**URL:** https://discourse.julialang.org/t/ann-abcdez-jl-bayesian-inference-model-evidences/99655
**Category:** Package Announcements
**Tags:** package, announcement, bayesian-inference
**Created:** [May 31, 2023, 8:03am UTC](https://discourse.julialang.org/t/ann-abcdez-jl-bayesian-inference-model-evidences/99655 "2023-05-31T08:03:15Z")
**Posts on this page:** 1
**Page:** 1

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### Author: ![mlanghinrichs](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/mlanghinrichs/32/50371_2.png) [@mlanghinrichs](https://discourse.julialang.org/u/mlanghinrichs)
#### Post date: [May 31, 2023, 8:03am UTC](https://discourse.julialang.org/t/ann-abcdez-jl-bayesian-inference-model-evidences/99655/1 "2023-05-31T08:03:15Z")

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Hi there,

I want to share a package that I have developed over the last months, for Approximate Bayesian Computation (ABC) / inference problems with an intractable likelihood. In ABC, models only need to be simulated (to circumvent the specification of a likelihood function), allowing for a broad application of Bayesian inference.

Reason for this implementation was the current lack (at least from what I have found) in ABC packages to compute model evidences as the basis for model selection/comparison (via model probabilities or Bayes Factors). ABCdeZ.jl comes with an algorithm for that, next to other features (please check the docs :)). Also be reminded of the usual caveats of ABC for model selection (see docs or wiki).

This required some modification of a previous SMC algorithm; as such ABCdeZ.jl adapts some code from [KissABC.jl](https://github.com/francescoalemanno/KissABC.jl). Big thanks for the developers of that package; I added a shared license file in ABCdeZ.jl.

I’m very happy to get feedback! The package is registered, if interested check it out here

> **[GitHub - mauricelanghinrichs/ABCdeZ.jl: Approximate Bayesian Computation...](https://github.com/mauricelanghinrichs/ABCdeZ.jl)**
>
> Approximate Bayesian Computation (ABC) with differential evolution (de) moves and model evidence (Z) estimates. - GitHub - mauricelanghinrichs/ABCdeZ.jl: Approximate Bayesian Computation (ABC) with...