A test statistic for graphical modelling of multivariate time series

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10 Citations (Scopus)

Abstract

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
JournalBiometrika
Volume93
Issue number2
DOIs
Publication statusPublished - 2006 Jun 1

Keywords

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

ASJC Scopus subject areas

  • Statistics and Probability
  • Mathematics(all)
  • Agricultural and Biological Sciences (miscellaneous)
  • Agricultural and Biological Sciences(all)
  • Statistics, Probability and Uncertainty
  • Applied Mathematics

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