Publication:
Boolean valued representation of random Sets and markov kernels with application to large deviations

Simple item page
dc.contributorZapata García, José Miguel
dc.contributor.authorAvilés López, Antonio
dc.contributor.departmentEstadística e Investigación Operativa
dc.date.accessioned2025-01-26T09:59:42Z
dc.date.available2025-01-26T09:59:42Z
dc.date.issued2020-10-20
dc.description© 2020 by the authors. 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 Mathematics. To access the final edited and published work see https://doi.org/10.3390/math8101848
dc.description.abstractWe establish a connection between random set theory and Boolean valued analysis by showing that random Borel sets, random Borel functions, and Markov kernels are respectively represented by Borel sets, Borel functions, and Borel probability measures in a Boolean valued model. This enables a Boolean valued transfer principle to obtain random set analogues of available theorems. As an application, we establish a Boolean valued transfer principle for large deviations theory, which allows for the systematic interpretation of results in large deviations theory as versions for Markov kernels. By means of this method, we prove versions of Varadhan and Bryc theorems, and a conditional version of Cramér theorem.es
dc.formatapplication/pdfes
dc.identifier.citationMathematics 2020, 8, 1848
dc.identifier.doihttps://doi.org/10.3390/math8101848
dc.identifier.issnElectronic: 2227-7390
dc.identifier.urihttp://hdl.handle.net/10201/149308
dc.languageenges
dc.publisherMDPI
dc.relationBecas MTM2017-86182-P, Fundación Séneca 20797/PI/18, Fundación Séneca 20903/PD/18.es
dc.relation.publisherversionhttps://www.mdpi.com/2227-7390/8/10/1848
dc.rightsinfo:eu-repo/semantics/openAccesses
dc.rightsAtribución 4.0 Internacional*
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/*
dc.subjectBoolean valued analysis
dc.subjectRandom sets
dc.subjectMarkov kernels
dc.subjectLarge deviations
dc.titleBoolean valued representation of random Sets and markov kernels with application to large deviationses
dc.typeinfo:eu-repo/semantics/articlees
dspace.entity.typePublicationes
Files
Original bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
2021-mathematics-Vol8-No10-1848.pdf
Size:
395.62 KB
Format:
Adobe Portable Document Format
Description:
Boolean Valued Representation of Random Sets and Markov Kernels with Application to Large Deviations
Download
License bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
license.txt
Size:
2.26 KB
Format:
Item-specific license agreed upon to submission
Description:
Download
Collections
Artículos