A motif building process for simulating random networks

Alan M. Polansky and Paramahansa Pramanik

Computational Statistics & Data Analysis, 2021, vol. 162, issue C

Abstract: A simple stochastic process is described which provides a useful basis for generating some types of random networks. The process is based on an iterative building block technique that uses a motif profile as a conditional probability model. The conditional iterative form of the algorithm insures that the calculations required to simulate an observed random network are relatively simple and does not require complicated models to be fit to an observed network. Bounds on the theoretical cohesiveness of the realized networks are established and empirical studies provide indications on more general properties of the resulting network, suggesting the types of applications where the process would be useful. The algorithm is used to generate networks similar to those observed in several examples.

Keywords: Markov process; Network statistics; Random graphs (search for similar items in EconPapers)
Date: 2021
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Citations: View citations in EconPapers (6)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:csdana:v:162:y:2021:i:c:s0167947321000979

DOI: 10.1016/j.csda.2021.107263

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