Estimation of Causal Orders in a Linear Non-Gaussian Acyclic Model: A Method Robust against Latent Confounders

@inproceedings{Tashiro2012EstimationOC,
  title={Estimation of Causal Orders in a Linear Non-Gaussian Acyclic Model: A Method Robust against Latent Confounders},
  author={Tatsuya Tashiro and Shohei Shimizu and Aapo Hyv{\"a}rinen and Takashi Washio},
  booktitle={ICANN},
  year={2012}
}
We consider learning a causal ordering of variables in a linear non-Gaussian acyclic model called LiNGAM. Several existing methods have been shown to consistently estimate a causal ordering assuming that all the model assumptions are correct. But, the estimation results could be distorted if some assumptions actually are violated. In this paper, we propose… CONTINUE READING