Detecting Confounders in Multivariate Time Series using Strength of Causation
Author:
Affiliation:
1. Department of Applied Mathematics and Statistics
2. Stony Brook University,Department of Electrical and Computer Engineering,NY,11794
Funder
National Science Foundation
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10289698/10289713/10289850.pdf?arnumber=10289850
Reference28 articles.
1. Detecting Confounding in Multivariate Linear Models via Spectral Analysis
2. Causal Inference Using the Algorithmic Markov Condition
3. We Are Not Your Real Parents: Telling Causal from Confounded using MDL
4. Detecting non-causal artifacts in multivariate linear regression models;janzing;International Conference on Machine Learning,0
5. Quantifying causal influences
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