Generating random networks from a given distribution

  • Authors:
  • Nathan Carter;Charles Hadlock;Dominique Haughton

  • Affiliations:
  • Mathematical Sciences Department, Bentley College, Waltham, MA 02452, United States;Mathematical Sciences Department, Bentley College, Waltham, MA 02452, United States;Mathematical Sciences Department, Bentley College, Waltham, MA 02452, United States

  • Venue:
  • Computational Statistics & Data Analysis
  • Year:
  • 2008

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Abstract

Several variations are given for an algorithm that generates random networks approximately respecting the probabilities given by any likelihood function, such as from a p^* social network model. A novel use of the genetic algorithm is incorporated in these methods, which improves its applicability to the degenerate distributions that can arise with p^* models. Our approach includes a convenient way to find the high-probability items of an arbitrary network distribution function.