Large deviations for the degree structure in preferential attachment schemes

Jihyeok Choi, Sunder Sethuraman

Research output: Contribution to journalArticlepeer-review

5 Scopus citations

Abstract

Preferential attachment schemes, where the selection mechanism is linear and possibly time-dependent, are considered, and an infinite-dimensional large deviation principle for the sample path evolution of the empirical degree distribution is found by Dupuis-Ellis-type methods. Interestingly, the rate function, which can be evaluated, contains a term which accounts for the cost of assigning a fraction of the total degree to an "infinite" degree component, that is, when an atypical "condensation" effect occurs with respect to the degree structure. As a consequence of the large deviation results, a sample path a.s. law of large numbers for the degree distribution is deduced in terms of a coupled system of ODEs from which power law bounds for the limiting degree distribution are given. However, by analyzing the rate function, one can see that the process can deviate to a variety of atypical nonpower law distributions with finite cost, including distributions typically associated with sub and superlinear selection models.

Original languageEnglish (US)
Pages (from-to)722-763
Number of pages42
JournalAnnals of Applied Probability
Volume23
Issue number2
DOIs
StatePublished - Apr 2013
Externally publishedYes

Keywords

  • Condensation
  • Degree distribution
  • Large deviations
  • Law of large numbers
  • Power law
  • Preferential attachment
  • Random graphs
  • Time-dependent

ASJC Scopus subject areas

  • Statistics and Probability
  • Statistics, Probability and Uncertainty

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