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Graphical Interaction Models for Multivariate Time Series

Dahlhaus, Rainer

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In this paper we extend the concept of graphical models for multivariate data to multivariate time series. We define a partial correlation graph for time series and use the partial spectral coherence between two components given the remaining components to identify the edges of the graph. As an example we consider multivariate autoregressive processes. The method is applied to air pollution data.

Item Type: Working paper
Place of Publication: Heidelberg
Date Deposited: 25 May 2016 13:05
Date: December 1999
Number of Pages: 21
Faculties / Institutes: The Faculty of Mathematics and Computer Science > Department of Applied Mathematics
Subjects: 510 Mathematics
Schriftenreihe ID: Beiträge zur Statistik > Beiträge
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