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Statistical analysis of change in networks

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  • O. Frank

Abstract

A survey is given of random graphs and random graph processes which can be used to describe and analyze networks that are changing with time. Marko‐vian change over time, log‐linear models for change, and conditionally uniform models for change are described. It is noted that estimation is usually complex if the random graph involves dependent dyads. Models with deterministic change over time may be a way to avoid the difficulties implied by dependent dyads. Logit regression methods are described that can be used to estimate such models.

Suggested Citation

  • O. Frank, 1991. "Statistical analysis of change in networks," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 45(3), pages 283-293, September.
    • Handle: RePEc:bla:stanee:v:45:y:1991:i:3:p:283-293
    DOI: 10.1111/j.1467-9574.1991.tb01310.x
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    Cited by:

    1. William Day & Rudolf Mathar & Ove Frank & R. Payne & Chris Glasbey & Carl Ramm & David Banks & Pascale Rousseau & Erhard Godehardt, 1996. "Book reviews," Journal of Classification, Springer;The Classification Society, vol. 13(2), pages 337-362, September.
    2. Javier Sánchez García & Salvador Cruz Rambaud, 2024. "The network econometrics of financial concentration," Review of Managerial Science, Springer, vol. 18(7), pages 2007-2045, July.
    3. Anna Malinovskaya & Philipp Otto, 2021. "Online network monitoring," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 30(5), pages 1337-1364, December.

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