On causal discovery with an equal-variance assumption
成果类型：
Article
署名作者：
Chen, Wenyu; Drton, Mathias; Wang, Y. Samuel
署名单位：
University of Washington; University of Washington Seattle; Technical University of Munich; University of Chicago
刊物名称：
BIOMETRIKA
ISSN/ISSBN：
0006-3444
DOI：
10.1093/biomet/asz049
发表日期：
2019
页码：
973980
关键词：
摘要：
Prior work has shown that causal structure can be uniquely identified from observational data when these follow a structural equation model whose error terms have equal variance. We show that this fact is implied by an ordering among conditional variances. We demonstrate that ordering estimates of these variances yields a simple yet state-of-the-art method for causal structure learning that is readily extendable to high-dimensional problems.