Graphical modelling and the Mahalanobis distance

Edward Bedrick

Journal of Applied Statistics, 2005, vol. 32, issue 9, 959-967

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.

Keywords: Discriminant analysis; distance between populations (search for similar items in EconPapers)
Date: 2005
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DOI: 10.1080/02664760500163680

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