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Sugeno Integral-Based Confidence Intervals for the Theoretical h-Index

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Strengthening Links Between Data Analysis and Soft Computing

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 315))

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Abstract

Sugeno integral-based confidence intervals for the theoretical h-index of a fixed-length sequence of i.i.d. random variables are derived. They are compared with other estimators of such a distribution characteristic in a Pareto i.i.d. model. It turns out that in the first case we obtain much wider intervals. It seems to be due to the fact that a Sugeno integral, which may be applied on any ordinal scale, is known to ignore too much information from cardinal-scale data being aggregated.

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Correspondence to Marek Gagolewski .

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Gagolewski, M. (2015). Sugeno Integral-Based Confidence Intervals for the Theoretical h-Index. In: Grzegorzewski, P., Gagolewski, M., Hryniewicz, O., Gil, M. (eds) Strengthening Links Between Data Analysis and Soft Computing. Advances in Intelligent Systems and Computing, vol 315. Springer, Cham. https://doi.org/10.1007/978-3-319-10765-3_28

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  • DOI: https://doi.org/10.1007/978-3-319-10765-3_28

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-10764-6

  • Online ISBN: 978-3-319-10765-3

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