tigramite

Tigramite is a causal inference for time series python package. It allows to efficiently estimate causal graphs from high-dimensional time series datasets (causal discovery) and to use graphs for robust forecasting and the estimation and prediction of direct, total, and mediated effects. Causal discovery is based on linear as well as non-parametric conditional independence tests applicable to discrete or continuously-valued time series. Also includes functions for high-quality plots of the results.

homepage: https://github.com/jakobrunge/tigramite

version	toolchain
5.2.8.2	foss/2023b

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