Abstract
A distance measure between Fisher information matrices is used to define a class of measures of multivariate dependence between the components of a random vector. Some basic properties are proved for this class of measures. Examples are given to illustrate that the class gives good measures under multivariate normal, multivariate inverted Dirichlet distribution, as well as the bivariate exponential distribution of Arnold and Strauss (1988. J. Amer. Statist. Assoc. 83, 522–527). An ordering of multivariate distributions, when marginals are fixed, is also introduced.
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