P. Birmpa

Learning Non-Gaussian SEMs with Conditional Risk, and Why the Direction of Recursion Matters

Variance-based methods recover a Gaussian linear structural equation model (SEM) with equal or suitably constrained error variances, either by recursively identifying the source nodes with smallest conditional variance (top-down method) or sink nodes with highest conditional variance (bottom-up method). We show that th...