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Fast Sequential Creation of Random Realizations of Degree Sequences

Published

Author(s)

Brian D. Cloteaux

Abstract

We examine the problem of creating a random realizations of very large degree sequences. While fast in practice, the Markov chain Monte Carlo (MCMC) method for selecting a realization has limited usefulness for creating large graphs because of memory constraints. Instead, we focus on sequential importance sampling (SIS) schemes for random graph creation. A difficulty with SIS schemes is assuring that they terminate in a reasonable amount of time. We introduce a new sampling method where we can guarantee termination while achieving speed comparable to the MCMC method.
Citation
Internet Mathematics
Volume
12
Issue
3

Keywords

random graph, degree sequence

Citation

Cloteaux, B. (2016), Fast Sequential Creation of Random Realizations of Degree Sequences, Internet Mathematics, [online], https://doi.org/10.1080/15427951.2016.1164768 (Accessed June 21, 2024)

Issues

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Created March 24, 2016, Updated November 10, 2018