Characterization of causal ancestral graphs for time series with latent confounders

In this paper, we introduce a novel class of graphical models for representing time-lag specific causal relationships and independencies of multivariate time series with unobserved confounders. We completely characterize these graphs and show that they constitute proper subsets of the currently empl...

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Veröffentlicht in:	The Annals of statistics 2024-02, Vol.52 (1), p.103
1. Verfasser:	Gerhardus, Andreas
Format:	Artikel
Sprache:	eng
Schlagworte:	Algorithms Causality Equivalence Graphical representations Graphs Knowledge representation Markov chains Set theory State of the art Time series
Online-Zugang:	Volltext
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