nicolagnecco/causalXtreme: Causal discovery in heavy-tailed models

Functions for causal structure learning based on the paper 'Causal discovery in heavy-tailed models' by Gnecco, Meinshausen, Peters, and Engelke, (2018) <arXiv:1908.05097>. Extremal ancestral search (EASE) is the main algorithm to recover the causal order of a heavy-tailed structural causal model (SCM). To compare EASE with other methods, we provide wrapper functions around LiNGAM-ICA, PC and PC-Rank algorithm.

install.packages("remotes")
remotes::install_github("nicolagnecco/causalXtreme")