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Full Conglomerability, Continuity and Marginal Extension

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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

We investigate fully conglomerable coherent lower previsions in the sense of Walley, and some particular cases of interest: envelopes of fully conglomerable linear previsions, envelopes of countably additive linear previsions and fully disintegrable linear previsions. We study the connections with continuity and countable super-additivity, and show that full conglomerability can be characterised in terms of a supremum of marginal extension models.

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Acknowledgments

The research reported in this paper has been supported by project TIN2014-59543-P.

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Correspondence to Enrique Miranda .

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Miranda, E., Zaffalon, M. (2017). Full Conglomerability, Continuity and Marginal Extension. 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_44

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  • DOI: https://doi.org/10.1007/978-3-319-42972-4_44

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-42971-7

  • Online ISBN: 978-3-319-42972-4

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