4 papers
Nonlinearity, Feedback and Uniform Consistency in Causal Structural Learning
Shuyan Wang
The goal of Causal Discovery is to find automated search methods for learning causal structures from observational data. In some cases all variables of the interested causal mechan…
A Uniformly Consistent Estimator of non-Gaussian Causal Effects Under the k-Triangle-Faithfulness Assumption
Shuyan Wang, Peter Spirtes
Kalisch and Bühlmann (2007) showed that for linear Gaussian models, under the Causal Markov Assumption, the Strong Causal Faithfulness Assumption, and the assumption of causal suff…
Causal Clustering for 1-Factor Measurement Models on Data with Various Types
Shuyan Wang
The tetrad constraint is a condition of which the satisfaction signals a rank reduction of a covariance submatrix and is used to design causal discovery algorithms that detects the…
Unifying Causal Models with Trek Rules
Shuyan Wang
In many scientific contexts, different investigators experiment with or observe different variables with data from a domain in which the distinct variable sets might well be relate…