Estimating causal effects from nonparanormal observational data

DOI10.1515/ijb-2018-0030MaRDI QIDQ6636177

S. M. Mahmoudi, Ernst C. Wit

Publication date: 12 November 2024

Published in: The International Journal of Biostatistics (Search for Journal in Brave)

zbMATH Keywords

causal effectsGaussian copulaPC-algorithmdirected acyclic graph (DAG)nonparanormal distribution

Mathematics Subject Classification ID

Applications of statistics to biology and medical sciences; meta analysis (62P10)

Cites Work

• Title not available (Why is that?)
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• Non-homogeneous dynamic Bayesian networks for continuous data
• Statistical inference of regulatory networks for circadian regulation
• Estimating high-dimensional intervention effects from observational data
• High-dimensional semiparametric Gaussian copula graphical models
• Estimating the effect of joint interventions from observational data in sparse high-dimensional settings
• PC algorithm for Gaussian copula graphical models
• Causal diagrams for empirical research
• 10.1162/153244302760200696
• 10.1162/153244303321897717
• Conditional expectation formulae for copulas

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