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Variational Inequalities for Arbitrary Multivariate Distributions

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  • Papadatos, N.
  • Papathanasiou, V.
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    Abstract

    Upper bounds for the total variation distance between two arbitrary multivariate distributions are obtained in terms of the correspondingw-functions. The results extend some previous inequalities satisfied by the normal distribution. Some examples are also given.

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    File URL: http://www.sciencedirect.com/science/article/B6WK9-45KNB4H-2/2/0ee8647add76a5700a270b3f22557401
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    Bibliographic Info

    Article provided by Elsevier in its journal Journal of Multivariate Analysis.

    Volume (Year): 67 (1998)
    Issue (Month): 2 (November)
    Pages: 154-168

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    Handle: RePEc:eee:jmvana:v:67:y:1998:i:2:p:154-168

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    Related research

    Keywords: Total variation distance; multivariate distributions; w-functions;

    References

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    1. Chou, Jine-Phone, 1988. "An identity for multidimensional continuous exponential families and its applications," Journal of Multivariate Analysis, Elsevier, vol. 24(1), pages 129-142, January.
    2. Papathanasiou, V., 1993. "Some Characteristic Properties of the Fisher Information Matrix via Cacoullos-Type Inequalities," Journal of Multivariate Analysis, Elsevier, vol. 44(2), pages 256-265, February.
    3. Cacoullos, T. & Papathanasiou, V., 1992. "Lower variance bounds and a new proof of the central limit theorem," Journal of Multivariate Analysis, Elsevier, vol. 43(2), pages 173-184, November.
    4. Papathanasiou, V., 1996. "Multivariate Variational Inequalities and the Central Limit Theorem," Journal of Multivariate Analysis, Elsevier, vol. 58(2), pages 189-196, August.
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    Cited by:
    1. Mikami, Toshio, 2004. "Covariance kernel and the central limit theorem in the total variation distance," Journal of Multivariate Analysis, Elsevier, vol. 90(2), pages 257-268, August.

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