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Graphical modelling and the Mahalanobis distance

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  • Edward Bedrick

Abstract

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.

Suggested Citation

  • Edward Bedrick, 2005. "Graphical modelling and the Mahalanobis distance," Journal of Applied Statistics, Taylor & Francis Journals, vol. 32(9), pages 959-967.
    • Handle: RePEc:taf:japsta:v:32:y:2005:i:9:p:959-967
    DOI: 10.1080/02664760500163680
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