Abstract
In this paper, a marginal-free measure of mutually complete dependence for discrete random vectors through subcopulas is defined, which generalizes the corresponding results for discrete random variables. Properties of the measure are studied and an estimator of the measure is introduced. Several examples are given for illustration of our results.
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Acknowledgments
We would like to thank Professor Hung T. Nguyen for introducing this interesting topic to us and referees for their valuable comments and suggestions which greatly improve this paper.
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Zhu, X., Wang, T., Choy, S.T.B., Autchariyapanitkul, K. (2018). Measures of Mutually Complete Dependence for Discrete Random Vectors. In: Kreinovich, V., Sriboonchitta, S., Chakpitak, N. (eds) Predictive Econometrics and Big Data. TES 2018. Studies in Computational Intelligence, vol 753. Springer, Cham. https://doi.org/10.1007/978-3-319-70942-0_22
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DOI: https://doi.org/10.1007/978-3-319-70942-0_22
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