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Master's Dissertation
DOI
https://doi.org/10.11606/D.45.2013.tde-19022014-195734
Document
Author
Full name
Tássio Naia dos Santos
E-mail
Institute/School/College
Knowledge Area
Date of Defense
Published
São Paulo, 2013
Supervisor
Committee
Kohayakawa, Yoshiharu (President)
Leonardi, Florencia Graciela
Martin, Daniel Morgato
Title in Portuguese
Grafos aleatórios exponenciais
Keywords in Portuguese
Cadeia de Markov
Combinatória
Grafos Aleatórios
Monte Carlo
Abstract in Portuguese
Estudamos o comportamento da familia aresta-triangulo de grafos aleatorios exponenciais (ERG) usando metodos de Monte Carlo baseados em Cadeias de Markov. Comparamos contagens de subgrafos e correlacoes entre arestas de ergs as de Grafos Aleatorios Binomiais (BRG, tambem chamados de Erdos-Renyi). E um resultado teorico conhecido que para algumas parametrizacoes os limites das contagens de subgrafos de ERGs convergem para os de BRGs, assintoticamente no numero de vertices [BBS11, CD11]. Observamos esse fenomeno em grafos com poucos (20) vertices em nossas simulacoes.
Title in English
Exponential Random Graphs
Keywords in English
Combinatorics
Markov Chain
Monte Carlo
Random Graphs
Abstract in English
We study the behavior of the edge-triangle family of exponential random graphs (ERG) using the Markov Chain Monte Carlo method. We compare ERG subgraph counts and edge correlations to those of the classic Binomial Random Graph (BRG, also called Erdos-Renyi model). It is a known theoretical result that for some parameterizations the limit ERG subgraph counts converge to those of BRGs, as the number of vertices grows [BBS11, CD11]. We observe this phenomenon on graphs with few (20) vertices in our simulations.
 
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Publishing Date
2014-03-17
 
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