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A motif building process for simulating random networks

Author

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  • Polansky, Alan M.
  • Pramanik, Paramahansa

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.

Suggested Citation

  • Polansky, Alan M. & Pramanik, Paramahansa, 2021. "A motif building process for simulating random networks," Computational Statistics & Data Analysis, Elsevier, vol. 162(C).
  • Handle: RePEc:eee:csdana:v:162:y:2021:i:c:s0167947321000979
    DOI: 10.1016/j.csda.2021.107263
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    References listed on IDEAS

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    1. Caimo, Alberto & Gollini, Isabella, 2020. "A multilayer exponential random graph modelling approach for weighted networks," Computational Statistics & Data Analysis, Elsevier, vol. 142(C).
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    Cited by:

    1. Masud Alam, 2021. "Heterogeneous Responses to the U.S. Narrative Tax Changes: Evidence from the U.S. States," Papers 2107.13678, arXiv.org.
    2. Masud Alam, 2021. "Time Varying Risk in U.S. Housing Sector and Real Estate Investment Trusts Equity Return," Papers 2107.10455, arXiv.org.
    3. Paramahansa Pramanik & Alan M. Polansky, 2024. "Optimization of a dynamic profit function using Euclidean path integral," SN Business & Economics, Springer, vol. 4(1), pages 1-20, January.
    4. Paramahansa Pramanik & Alan M. Polansky, 2023. "Scoring a Goal Optimally in a Soccer Game Under Liouville-Like Quantum Gravity Action," SN Operations Research Forum, Springer, vol. 4(3), pages 1-39, September.

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