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A suggestion for a multivariate concordance coefficient

  • Silvia Terzi
  • Luca Moroni


In the present paper we will introduce a coecient of multivariate association i.e. association in a d-variate vector of observations x = (x1; : : : ; xd), where d  2 and where each xj is itself a vector of n observations. We order the observations, divide them in slices and count how many times one observation in the r-th slice of any of the d distributions also belongs to the r-th slice of any of the others. The greater the number of overlaps between the units belonging to corresponding slices, the greater the concordance between the d distributions. This is the simple and intuitive idea our multivariate association coecient  stems from. It is in fact a multidimensional concordance coecient since it assumes comonotonicity for all variables.

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Paper provided by Department of Economics - University Roma Tre in its series Departmental Working Papers of Economics - University 'Roma Tre' with number 0189.

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Date of creation: Apr 2014
Date of revision:
Handle: RePEc:rtr:wpaper:0189
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  1. M. Taylor, 2007. "Multivariate measures of concordance," Annals of the Institute of Statistical Mathematics, Springer, vol. 59(4), pages 789-806, December.
  2. Koen DECANCQ, 2010. "Copula-based orderings of multivariate dependence," Center for Economic Studies - Discussion papers ces10.08, Katholieke Universiteit Leuven, Centrum voor Economische Studiën.
  3. repec:sae:ecolab:v:16:y:2006:i:2:p:1-2 is not listed on IDEAS
  4. Nikolay Nenovsky & S. Statev, 2006. "Introduction," Post-Print halshs-00260898, HAL.
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