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Semi-Markov Graph Dynamics

In 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...

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Detalles Bibliográficos
Autores principales: Raberto, Marco, Rapallo, Fabio, Scalas, Enrico
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2011
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3160851/
https://www.ncbi.nlm.nih.gov/pubmed/21887245
http://dx.doi.org/10.1371/journal.pone.0023370
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author Raberto, Marco
Rapallo, Fabio
Scalas, Enrico
author_facet Raberto, Marco
Rapallo, Fabio
Scalas, Enrico
author_sort Raberto, Marco
collection PubMed
description In 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.
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spelling pubmed-31608512011-09-01 Semi-Markov Graph Dynamics Raberto, Marco Rapallo, Fabio Scalas, Enrico PLoS One Research Article In 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. Public Library of Science 2011-08-24 /pmc/articles/PMC3160851/ /pubmed/21887245 http://dx.doi.org/10.1371/journal.pone.0023370 Text en Raberto et al. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited.
spellingShingle Research Article
Raberto, Marco
Rapallo, Fabio
Scalas, Enrico
Semi-Markov Graph Dynamics
title Semi-Markov Graph Dynamics
title_full Semi-Markov Graph Dynamics
title_fullStr Semi-Markov Graph Dynamics
title_full_unstemmed Semi-Markov Graph Dynamics
title_short Semi-Markov Graph Dynamics
title_sort semi-markov graph dynamics
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3160851/
https://www.ncbi.nlm.nih.gov/pubmed/21887245
http://dx.doi.org/10.1371/journal.pone.0023370
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