CausalInference.jl
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mschauer
Causal inference, graphical models and structure learning in Julia
in https://mschauer.github.io/CausalInference.jl/latest/examples/backdoor_example/ (not against hand-drawn, actually, but they are a bit difficult to read)
Remove unnecessary `::Float64` constraints, e.g see comment in #68
High effort PR, but rewarding and a straight solution: The problem is as follows: There are two variables X and Y and we want to know the effect of X...
Improve documentation on DAG models, see https://r-causal.github.io/ggdag/articles/intro-to-dags.html for a nice example.
implemented permutation-based independence tests for categorical variables based on mutual information and conditional mutual information open questions: - can type information be used more elegantly/efficiently? - is the conditional mutual...
For DAGs: https://arxiv.org/pdf/1203.3515.pdf More general for CPDAG/MAG/PAG: https://auai.org/uai2015/proceedings/papers/155.pdf
It would be nice to have a Julia-native implementation of the (relatively) new PCMCI [1] algorithm for causal inference in time series proposed by @jakobrunge and his team. The algorithm...
Contributions, comments and feature requests are most welcome. The vanilla PC algorithm, the Markov skeleton algorithm and a function to check `d`-separation for directed graphs are implemented. Regards! Tagging @tfgit,...
### Description When running the [example code](https://mschauer.github.io/CausalInference.jl/latest/#Example-1), core dumped when calling functions in CausalInference.jl. ### How to reproduce ```shell julia> using Distributions, CausalInference, LightGraphs, DelimitedFiles, LinearAlgebra, Statistics julia> p =...
https://github.com/mschauer/CausalInference.jl/blob/master/test/klentropy.jl needs `Random.sees!(nnn)`, otherwise it will fail randomly. Maybe this applies to some more points