CausalityTools.jl is a package for quantifying associations and dynamical coupling between datasets, independence testing and causal inference.
All further information is provided in the
documentation, which you can either
find online or build locally by running the
- Association measures from conventional statistics, information theory and dynamical systems theory, for example distance correlation, mutual information, transfer entropy, convergent cross mapping and a lot more!
- A dedicated API for independence testing, which comes with automatic compatibility with
every measure-estimator combination you can think of. For example, we offer the generic
SurrogateTest, which is fully compatible with TimeseriesSurrogates.jl, and the
LocalPermutationTestfor conditional indepencence testing.
- A dedicated API for causal network inference based on these measures and independence tests.
To install the package, run
import Pkg; Pkg.add("CausalityTools").