High-dimensional causal discovery under non-Gaussianity

DOI10.1093/biomet/asz055zbMath1435.62213arXiv1803.11273OpenAlexW2981623184MaRDI QIDQ5222218

Y. Samuel Wang, Mathias Drton

Publication date: 1 April 2020

Published in: Biometrika (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1803.11273

zbMATH Keywords

high-dimensional statisticsstructural equation modelcausal discoverynon-Gaussian datadirected graphical model

Mathematics Subject Classification ID

Order statistics; empirical distribution functions (62G30) Probabilistic graphical models (62H22)

Related Items (5)

Learning high-dimensional Gaussian linear structural equation models with heterogeneous error variances ⋮ Efficient Learning of Quadratic Variance Function Directed Acyclic Graphs via Topological Layers ⋮ Unnamed Item ⋮ Causal structure learning: a combinatorial perspective ⋮ Multi-Trek Separation in Linear Structural Equation Models

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