On Causal Discovery with Equal Variance Assumption

07/09/2018
by   Mathias Drton, et al.
0

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 variances. 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.

READ FULL TEXT

Please sign up or login with your details

Forgot password? Click here to reset