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dc.contributor.authorRaberto, M.
dc.contributor.authorRapallo, F.
dc.contributor.authorScalas, E. 
dc.date.accessioned2017-02-21T08:18:16Z
dc.date.available2017-02-21T08:18:16Z
dc.date.issued2011-12-31
dc.identifier.issn1932-6203
dc.identifier.urihttp://hdl.handle.net/20.500.11824/474
dc.description.abstractIn this paper, we outline a model of graph (or network) dynamics based on two ingredients. The first ingredient is a Markov chain on the space of possible graphs. The second ingredient is a semi-Markov counting process of renewal type. The model consists in subordinating the Markov chain to the semi-Markov counting process. In simple words, this means that the chain transitions occur at random time instants called epochs. The model is quite rich and its possible connections with algebraic geometry are briefly discussed. Moreover, for the sake of simplicity, we focus on the space of undirected graphs with a fixed number of nodes. However, in an example, we present an interbank market model where it is meaningful to use directed graphs or even weighted graphs.
dc.formatapplication/pdf
dc.language.isoengen_US
dc.rightsReconocimiento-NoComercial-CompartirIgual 3.0 Españaen_US
dc.rights.urihttp://creativecommons.org/licenses/by-nc-sa/3.0/es/en_US
dc.titleSemi-markov graph dynamics
dc.typeinfo:eu-repo/semantics/articleen_US
dc.identifier.doi10.1371/journal.pone.0023370
dc.relation.publisherversionhttps://www.scopus.com/inward/record.uri?eid=2-s2.0-80052057453&doi=10.1371%2fjournal.pone.0023370&partnerID=40&md5=03d6f564b219866ac1c7317fc41a7947
dc.rights.accessRightsinfo:eu-repo/semantics/openAccessen_US
dc.type.hasVersioninfo:eu-repo/semantics/publishedVersionen_US
dc.journal.titlePLoS ONEen_US


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Reconocimiento-NoComercial-CompartirIgual 3.0 España
Except where otherwise noted, this item's license is described as Reconocimiento-NoComercial-CompartirIgual 3.0 España