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dc.contributor.author
Iglesias, Rodrigo Alejandro  
dc.contributor.author
Tohmé, Fernando Abel  
dc.contributor.author
Auday, Marcelo Roberto  
dc.date.available
2018-09-21T23:15:59Z  
dc.date.issued
2016-09  
dc.identifier.citation
Iglesias, Rodrigo Alejandro; Tohmé, Fernando Abel; Auday, Marcelo Roberto; Contextuality Scenarios Arising from Networks of Stochastic Processes; Springer; Open Systems & Information Dynamics; 23; 3; 9-2016; 15-29  
dc.identifier.issn
1230-1612  
dc.identifier.uri
http://hdl.handle.net/11336/60694  
dc.description.abstract
An empirical model is a generalization of a probability space. It consists of a simplicial complex of subsets of a class of random variables such that each simplex has an associated probability distribution. The ensuing marginalizations are coherent, in the sense that the distribution on a face of a simplex coincides with the marginal of the distribution over the entire simplex. An empirical model is called contextual if its distributions cannot be obtained by marginalizing a joint distribution over . Contextual empirical models arise naturally in quantum theory, giving rise to some of its counter -intuitive statistical consequences. In this paper, we present a different and classical source of contextual empirical models: the interaction among many stochastic processes. We attach an empirical model to the ensuing network in which each node represents an open stochastic process with input and output random variables. The statistical behaviour of the network in the long run makes the empirical model generically contextual and even strongly contextual.  
dc.format
application/pdf  
dc.language.iso
eng  
dc.publisher
Springer  
dc.rights
info:eu-repo/semantics/openAccess  
dc.rights.uri
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/  
dc.subject
Contextuality  
dc.subject
Empirical Models  
dc.subject
Open Stochastic Processes  
dc.subject.classification
Ciencias de la Computación  
dc.subject.classification
Ciencias de la Computación e Información  
dc.subject.classification
CIENCIAS NATURALES Y EXACTAS  
dc.title
Contextuality Scenarios Arising from Networks of Stochastic Processes  
dc.type
info:eu-repo/semantics/article  
dc.type
info:ar-repo/semantics/artículo  
dc.type
info:eu-repo/semantics/publishedVersion  
dc.date.updated
2018-09-18T14:23:35Z  
dc.journal.volume
23  
dc.journal.number
3  
dc.journal.pagination
15-29  
dc.journal.pais
Alemania  
dc.journal.ciudad
Berlín  
dc.description.fil
Fil: Iglesias, Rodrigo Alejandro. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Matemática Bahía Blanca. Universidad Nacional del Sur. Departamento de Matemática. Instituto de Matemática Bahía Blanca; Argentina  
dc.description.fil
Fil: Tohmé, Fernando Abel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Matemática Bahía Blanca. Universidad Nacional del Sur. Departamento de Matemática. Instituto de Matemática Bahía Blanca; Argentina. Universidad Nacional del Sur. Departamento de Economía; Argentina  
dc.description.fil
Fil: Auday, Marcelo Roberto. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Investigaciones Económicas y Sociales del Sur. Universidad Nacional del Sur. Departamento de Economía. Instituto de Investigaciones Económicas y Sociales del Sur; Argentina. Universidad Nacional del Sur. Departamento de Humanidades; Argentina  
dc.journal.title
Open Systems & Information Dynamics  
dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/url/https://www.worldscientific.com/doi/abs/10.1142/S1230161216500128  
dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/doi/http://dx.doi.org/10.1142/S1230161216500128