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Learning Causal Relations in Multivariate Time Series Data
2007
Economics : the Open-Access, Open-Assessment e-Journal
Applying a probabilistic causal approach, we define a class of time series causal models (TSCM) based on stationary Bayesian networks. A TSCM can be seen as a structural VAR identified by the causal relations among the variables. We classify TSCMs into observationally equivalent classes by providing a necessary and sufficient condition for the observational equivalence. Applying an automated learning algorithm, we are able to consistently identify the data-generating causal structure up to the
doi:10.5018/economics-ejournal.ja.2007-11
fatcat:l5zrjhk4qbbgvhhprxmg3jqycy