Estimating the effect of joint interventions from observational data in sparse high-dimensional settings
From MaRDI portal
Publication:2012201
DOI10.1214/16-AOS1462zbMath1426.62286arXiv1407.2451OpenAlexW2963772919MaRDI QIDQ2012201
Preetam Nandy, Marloes H. Maathuis, Thomas S. Richardson
Publication date: 28 July 2017
Published in: The Annals of Statistics (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/1407.2451
directed acyclic graphhigh-dimensional datacausal inferencelinear structural equation modeljoint causal effectsmultiple simultaneous interventionsnonparanormal distribution
Estimation in multivariate analysis (62H12) Applications of statistics to biology and medical sciences; meta analysis (62P10) Inference from stochastic processes (62M99)
Related Items
A local method for identifying causal relations under Markov equivalence, An overview of heavy-tail extensions of multivariate Gaussian distribution and their relations, Testing Mediation Effects Using Logic of Boolean Matrices, An unbiased estimator of the causal effect on the variance based on the back-door criterion in Gaussian linear structural equation models, Bayesian causal inference in probit graphical models, Structural Intervention Distance for Evaluating Causal Graphs, Variance formulas for estimated mean response and predicted response with external intervention based on the back-door criterion in linear structural equation models, High-dimensional consistency in score-based and hybrid structure learning, Complete Graphical Characterization and Construction of Adjustment Sets in Markov Equivalence Classes of Ancestral Graphs, Structural learning and estimation of joint causal effects among network-dependent variables, Robust Causal Structure Learning with Some Hidden Variables, Unnamed Item
