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

Budny Katarzyna ()
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Budny Katarzyna: Cracow University of Economics, ; Cracow, ; Poland

Statistics in Transition New Series, 2017, vol. 18, issue 1, 1-20

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.

Keywords: central moment of a random vector; estimator; multivariate distribution; power of a vector (search for similar items in EconPapers)
Date: 2017
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Persistent link: https://EconPapers.repec.org/RePEc:vrs:stintr:v:18:y:2017:i:1:p:1-20:n:7

DOI: 10.21307/stattrans-2016-061

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