Abstract
Since the Aumann-type expected value of a random interval is not robust, the aim of this paper is to propose a new central tendency measure for interval-valued data. The median of a random interval has already been defined as the interval minimizing the mean distance, in terms of an L 1 metric extending the Euclidean distance, to the values of the random interval. Inspired by the spatial median, we now follow a more common approach to define the median using an L 2 metric.
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Sinova, B., González-Rodríguez, G., Van Aelst, S. (2013). An Alternative Approach to the Median of a Random Interval Using an L 2 Metric. In: Kruse, R., Berthold, M., Moewes, C., Gil, M., Grzegorzewski, P., Hryniewicz, O. (eds) Synergies of Soft Computing and Statistics for Intelligent Data Analysis. Advances in Intelligent Systems and Computing, vol 190. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-33042-1_30
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DOI: https://doi.org/10.1007/978-3-642-33042-1_30
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-33041-4
Online ISBN: 978-3-642-33042-1
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