Journal of the Korean Statistical Society

The Korean Statistical Society (한국통계학회)
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A BAYESIAN METHOD FOR FINDING MINIMUM GENERALIZED VARIANCE AMONG K MULTIVARIATE NORMAL POPULATIONS

  • Published : 2003.12.01
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Abstract

In this paper we develop a method for calculating a probability that a particular generalized variance is the smallest of all the K multivariate normal generalized variances. The method gives a way of comparing K multivariate populations in terms of their dispersion or spread, because the generalized variance is a scalar measure of the overall multivariate scatter. Fully parametric frequentist approach for the probability is intractable and thus a Bayesian method is pursued using a variant of weighted Monte Carlo (WMC) sampling based approach. Necessary theory involved in the method and computation is provided.

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