Abstract
Friedman’s test is traditionally applied for testing independence between k orderings (k > 2). In the paper we show how to generalize Friedman’s test for situations with missing information or non-comparable outputs. This contribution is a corrected version of our previous paper [8].
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© 2006 Springer
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Mrówka, E., Grzegorzewski, P. (2006). Friedman’s Test for Ambiguous and Missing Data. In: Lawry, J., et al. Soft Methods for Integrated Uncertainty Modelling. Advances in Soft Computing, vol 37. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-34777-1_15
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DOI: https://doi.org/10.1007/3-540-34777-1_15
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-34776-7
Online ISBN: 978-3-540-34777-4
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