A test statistic for graphical modelling of multivariate time series

Research output: Contribution to journalArticlepeer-review

14 Citations (Scopus)


A graphical model for multivariate time series is a concept extended by Dahlhaus (2000) from that for a random vector to a multivariate time series. We propose a test statistic for identifying the model based on the Kullback-Leibler divergence between two graphical models. The null distribution is shown to be asymptotically normal with mean and variance which depend just on the dimensions of the graphs.

Original languageEnglish
Pages (from-to)399-409
Number of pages11
Issue number2
Publication statusPublished - 2006 Jun


  • Asymptotic normality
  • Backward stepwise selection
  • Conditional independence
  • Graphical model
  • Kullback-Liebler divergence
  • Periodogram
  • Spectral density matrix
  • Test statistic


Dive into the research topics of 'A test statistic for graphical modelling of multivariate time series'. Together they form a unique fingerprint.

Cite this