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A Sandwich Theorem for Natural Extensions

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Soft Methods for Data Science (SMPS 2016)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 456))

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Abstract

The recently introduced weak consistency notions of 2-coherence and 2-convexity are endowed with a concept of 2-coherent, respectively, 2-convex natural extension, whose properties parallel those of the natural extension for coherent lower previsions. We show that some of these extensions coincide in various common instances, thus producing the same inferences.

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References

  1. de Finetti B (1974) Theory of probability. Wiley

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  5. Pelessoni R, Vicig P (2016) \(2\)-coherent and \(2\)-convex conditional lower previsions. Submitted

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Acknowledgments

We acknowledge partial support by the FRA2015 grant ‘Mathematical Models for Handling Risk and Uncertainty’.

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Authors and Affiliations

  1. DEAMS ‘B. de Finetti’, University of Trieste, Piazzale Europa 1, 34127, Trieste, Italy

    Renato Pelessoni & Paolo Vicig

Authors
  1. Renato Pelessoni
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  2. Paolo Vicig
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Corresponding author

Correspondence to Renato Pelessoni .

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Editors and Affiliations

  1. Department of Statistical Sciences, Sapienza University of Rome, Rome, Italy

    Maria Brigida Ferraro

  2. Department of Statistical Sciences, Sapienza University of Rome, Roma, Italy

    Paolo Giordani

  3. Dept of Basic & Applied Sciences Engg, Sapienza University of Rome, Rome, Italy

    Barbara Vantaggi

  4. Dept of Stoc Metds,Polish Academy of Sci, Systems Research Institute, Warsaw, Poland

    Marek Gagolewski

  5. Dept of Statis&OR and MD, Univ de Oviedo, Oviedo, Spain

    María Ángeles Gil

  6. Dept of Stoc Metds,Polish Aca of Science, Systems Res Inst, Warsaw, Poland

    Przemysław Grzegorzewski

  7. Sys Res Inti, Dept of Stoch Methods, Polish Acadmy Sci in Warsaw, Warsaw, Poland

    Olgierd Hryniewicz

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Pelessoni, R., Vicig, P. (2017). A Sandwich Theorem for Natural Extensions. 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_48

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  • DOI: https://doi.org/10.1007/978-3-319-42972-4_48

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-42971-7

  • Online ISBN: 978-3-319-42972-4

  • eBook Packages: EngineeringEngineering (R0)

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