Abstract
After introducing a definition of dispersion measure on the Euclidean space \(\mathbb {R}^k\), we deal with the connection between these measures and the so called multidistances. In this way, we show that thr standard deviation is a relevant example of multidistance and, on the other hand, several significant families of multidistances are, at the same time, dispersion measures. Sufficient conditions for a multidistance to be a dispersion measure are also established.
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References
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Acknowledgments
This work has been supported by the Spanish Government projects TIN2013-42795-P and TIN2014-56381-REDT (LODISCO).
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Martín, J., Mayor, G. (2017). Dispersion Measures and Multidistances on \(\mathbb {R}^k\) . In: Ferraro, M., et al. Soft Methods for Data Science. SMPS 2016. Advances in Intelligent Systems and Computing, vol 456. Springer, Cham. https://doi.org/10.1007/978-3-319-42972-4_43
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DOI: https://doi.org/10.1007/978-3-319-42972-4_43
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