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  • 标题:Exponential Approximation, Method of Types for Empirical Neighbourhood Distributions of Random Graphs by Random Allocations
  • 作者:K. Doku-Amponsah
  • 期刊名称:International Journal of Statistics and Probability
  • 印刷版ISSN:1927-7032
  • 电子版ISSN:1927-7040
  • 出版年度:2014
  • 卷号:3
  • 期号:2
  • 页码:110
  • DOI:10.5539/ijsp.v3n2p110
  • 出版社:Canadian Center of Science and Education
  • 摘要:In this article we find exponential good approximation of the empirical neigbourhood distribution of symbolled random graphs conditioned to a given empirical symbol distribution and empirical pair distribution. Using this approximation we shorten or simplify the proof of (Doku-Amponsah \& Morters, 2010, Theorem~2.5); the large deviation principle (LDP) for empirical neigbourhood distribution of symbolled random graphs. We also show that the LDP for the empirical degree measure of the classical Erd\H{o}s-R\'{e}nyi graph is a special case of (Doku-Amponsah \& Moerters, 2010, Theorem~2.5). From the LDP for the empirical degree measure, we derive an LDP for the the proportion of isolated vertices in the classical Erd\H{o}s-R\'{e}nyi graph.
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