Collection of algorithms related to the detection of underlying causal structure from time series data, and for the approximation of the transfer operator and invariant measures.



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CausalityTools.jl provides tools for nonparametric detection of causal relationships between dynamical variables based on time series of observations.

Check out the documentation for more information!

Key features

The package is equally well-suited both for the study of causal directionality for experimental data, and for studying theoretical systems. Key features include:


CausalityTools.jl is a registered julia package, you can therefore add the latest tagged release by running the following lines in the Julia console.

import Pkg; Pkg.add("CausalityTools")

For the latest development version of the package, add the package by referring directly to the GitHub repository.

import Pkg; Pkg.add("https://github.com/kahaaga/CausalityTools.jl/")

Fixing SpecialFunction.jl error

During installation, you might get an error related to SpecialFunctions.jl. If so, just run the following:


Then run

using CausalityTools

to verify that everything works.

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