Tigramite is a causal time series analysis python package. It allows to efficiently reconstruct causal graphs from high-dimensional time series datasets and model the obtained causal dependencies for causal mediation and prediction analyses. Causal discovery is based on linear as well as non-parametric conditional independence tests applicable to discrete or continuously-valued time series. Currently, tigramite cannot identify causal directionality for contemporaneous links which are left undirected. Also includes functions for high-quality plots of the results.

More Information

For more information visit the tigramite website.

Available Versions

These versions of tigramite are available on the BEAR systems (BlueBEAR, BEAR Cloud VMs, and CaStLeS VMs). These will be retained in accordance with our Applications Support and Retention Policy.

Version BEAR Apps Version
4.0.0-beta-foss-2018b-Python-3.6.6 2018b