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.
Package details |
|
---|---|
Maintainer | |
License | GPL-3 |
Version | 0.0.0.9000 |
URL | https://github.com/nicolagnecco/causalXtreme |
Package repository | View on GitHub |
Installation |
Install the latest version of this package by entering the following in R:
|
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.