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Estimation of the Central Moments of a Random Vector Based on the Definition of the Power of a Vector

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  • Budny Katarzyna

    (Cracow University of Economics, ; Cracow, ; Poland)

Abstract

The moments of a random vector based on the definition of the power of a vector, proposed by J. Tatar, are scalar and vector characteristics of a multivariate distribution. Analogously to the univariate case, we distinguish the uncorrected and the central moments of a random vector. Other characteristics of a multivariate distribution, i.e. an index of skewness and kurtosis, have been introduced by using the central moments of a random vector. For the application of the mentioned quantities for the analysis of multivariate empirical data, it appears desirable to construct their respective estimators.

Suggested Citation

  • Budny Katarzyna, 2017. "Estimation of the Central Moments of a Random Vector Based on the Definition of the Power of a Vector," Statistics in Transition New Series, Polish Statistical Association, vol. 18(1), pages 1-20, March.
    • Handle: RePEc:vrs:stintr:v:18:y:2017:i:1:p:1-20:n:7
    DOI: 10.21307/stattrans-2016-061
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