# AnalyticComb.jl - Analytic Combinatorics in Julia

**URL:** <https://discourse.julialang.org/t/analyticcomb-jl-analytic-combinatorics-in-julia/104196>\
**Category:** Package Announcements\
**Tags:** combinatorics, symbolics\
**Created:** [September 24, 2023, 3:02pm UTC](https://discourse.julialang.org/t/analyticcomb-jl-analytic-combinatorics-in-julia/104196 "2023-09-24T15:02:27Z")\
**Posts on this page:** 1\
**Showing post:** 10

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**Author:** ![fargolo](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/fargolo/32/37515_2.png) [@fargolo](https://discourse.julialang.org/u/fargolo)\
**Post date:** [May 30, 2024, 2:18pm UTC](https://discourse.julialang.org/t/analyticcomb-jl-analytic-combinatorics-in-julia/104196/10 "2024-05-30T14:18:38Z")

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@lrnv

Take a look at this first application for time-series:

> [@Time-series analysis - Probabilistic inference on RQA ( SymbolicInference.jl)](https://discourse.julialang.org/t/time-series-analysis-probabilistic-inference-on-rqa-symbolicinference-jl/114701):
>
> [How it started](https://discourse.julialang.org/t/analyticcomb-jl-analytic-combinatorics-in-julia/104196) The [SymbolicInference.jl package](https://github.com/fargolo/SymbolicInference.jl) uses [Analytic Combinatorics](https://github.com/fargolo/AnalyticComb.jl) to perform probabilistic inference over certain combinatorial classes. The first application is explained in this white paper [Probabilistic inference on arbitrary time-series via symbolic methods: exploring complex dynamics with analytics combinatorics and recurrence analysis](https://osf.io/preprints/osf/3ws85). It tackles time series analysis using combinatorial specifications for binary words to handle binary matrices from recurrence quantification ana…

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