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Kendall regression coefficient

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  • Liebscher, Eckhard

Abstract

A new multivariate extension of Kendall’s dependence coefficient tailored for use in regression analysis is introduced. This coefficient is called Kendall regression coefficient and indicates how well the response variable can be approximated by a strictly increasing function of the regressor (predictor) variables. The properties of this coefficient are examined. In the second part the empirical regression coefficient is considered. It is proved that this coefficient is asymptotically normally distributed.

Suggested Citation

  • Liebscher, Eckhard, 2021. "Kendall regression coefficient," Computational Statistics & Data Analysis, Elsevier, vol. 157(C).
    • Handle: RePEc:eee:csdana:v:157:y:2021:i:c:s0167947320302310
    DOI: 10.1016/j.csda.2020.107140
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    References listed on IDEAS

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    5. Marco Scarsini, 1984. "On measures of concordance," Post-Print hal-00542380, HAL.
    6. Grothe, Oliver & Schnieders, Julius & Segers, Johan, 2014. "Measuring association and dependence between random vectors," Journal of Multivariate Analysis, Elsevier, vol. 123(C), pages 96-110.
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