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dc.contributor.authorKupper, Michael-
dc.contributor.authorZapata García, José Miguel-
dc.date.accessioned2025-01-26T10:04:59Z-
dc.date.available2025-01-26T10:04:59Z-
dc.date.issued2023-03-22-
dc.identifier.citationFuzzy Sets and Systems 467(2023) 108506es
dc.identifier.issnPrint: 0165-0114-
dc.identifier.urihttp://hdl.handle.net/10201/149290-
dc.description© 2023 The Author(s). This manuscript version is made available under the CC-BY 4.0 license http://creativecommons.org/licenses/by/4.0/. This document is the Published version of a Published Work that appeared in final form in Fuzzy Sets and Systems. To access the final edited and published work see https://doi.org/10.1016/j.fss.2023.03.009-
dc.description.abstractThe Shilkret integral with respect to a completely maxitive capacity is fully determined by a possibility distribution. In this paper, we introduce a weaker topological form of maxitivity and show that under this assumption the Shilkret integral is still determined by its possibility distribution for functions that are sufficiently regular. Motivated by large deviations theory, we provide a Laplace principle for maxitive integrals and characterize the possibility distribution under certain separation and convexity assumptions. Moreover, we show a maxitive integral representation result for weakly maxitive non-linear expectations. The theoretical results are illustrated by providing large deviations bounds for sequences of capacities, and by deriving a monotone analogue of Cramér's theorem.es
dc.formatapplication/pdfes
dc.format.extent27es
dc.languageenges
dc.publisherElsevieres
dc.relationSin financiación externa a la Universidades
dc.rightsinfo:eu-repo/semantics/openAccesses
dc.rightsAtribución 4.0 Internacional*
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/*
dc.subjectShilkret integrales
dc.subjectCapacityes
dc.subjectPossibility distributiones
dc.subjectWeak maxitivityes
dc.subjectLarge deviation principlees
dc.subjectLaplace principlees
dc.titleWeakly maxitive set functions and their possibility distributionses
dc.typeinfo:eu-repo/semantics/articlees
dc.relation.publisherversionhttps://www.sciencedirect.com/science/article/pii/S0165011423001318?via%3Dihub-
dc.identifier.doihttps://doi.org/10.1016/j.fss.2023.03.009-
dc.contributor.departmentDepartamento de Estadística e Investigación Operativa-
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