Metrika

, Volume 51, Issue 2, pp 157–172 | Cite as

Graphical interaction models for multivariate time series1

  • Rainer Dahlhaus

Abstract.

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.

Key words: Graphical models, multivariate time series, partial spectral coherence, spectral estimates, multivariate autoregressive processes, air pollution data. 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2000

Authors and Affiliations

  • Rainer Dahlhaus
    • 1
  1. 1.Universität Heidelberg, Institut für Angewandte Mathematik, Im Neuenheimer Feld 294, 69120 Heidelberg, Germany (e-mail: dahlhaus@statlab.uni-heidelberg.de)DE

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