Graphical modelling and the Mahalanobis distance

Research output: Contribution to journalArticlepeer-review

4 Scopus citations


I consider the problem of estimating the Mahalanobis distance between multivariate normal populations when the population covariance matrix satisfies a graphical model. In addition to providing a clear understanding of the dependencies in a multivariate data set, the use of graphical models can reduce the variability of the estimated distances and improve inferences. I derive the asymptotic distribution of the estimated Mahalanobis distance under a general covariance model, which includes graphical models as a special case. Two examples are discussed.

Original languageEnglish (US)
Pages (from-to)959-967
Number of pages9
JournalJournal of Applied Statistics
Issue number9
StatePublished - Nov 2005
Externally publishedYes


  • Discriminant analysis
  • Distance between populations

ASJC Scopus subject areas

  • Statistics and Probability
  • Statistics, Probability and Uncertainty


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