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Missing Data Augmentation for Bayesian Exponential Random Multi-Graph Models

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Complex Networks X (CompleNet 2019)

Part of the book series: Springer Proceedings in Complexity ((SPCOM))

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Abstract

In this paper we present an estimation algorithm for Bayesian exponential random multi-graphs (BERmGMs) under missing network data. Social actors are often connected with more than one type of relation, thus forming a multiplex network. It is important to consider these multiplex structures simultaneously when analyzing a multiplex network. The importance of proper models of multiplex network structures is even more pronounced under the issue of missing network data. The proposed algorithm is able to estimate BERmGMs under missing data and can be used to obtain proper multiple imputations for multiplex network structures. It is an extension of Bayesian exponential random graphs (BERGMs) as implemented in the Bergm package in R. We demonstrate the algorithm on a well-known example, with and without artificially simulated missing data.

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Acknowledgements

We would like to thank the Center for Information Technology of the University of Groningen for their support and for providing access to the Peregrine high performance computing cluster.

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Authors and Affiliations

  1. University of Groningen, Groningen, The Netherlands

    Robert W. Krause

  2. Dublin Institute of Technology, Dublin, Ireland

    Alberto Caimo

Authors
  1. Robert W. Krause
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  2. Alberto Caimo
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Corresponding author

Correspondence to Robert W. Krause .

Editor information

Editors and Affiliations

  1. Center for Complex Network Research, Northeastern University, Boston, MA, USA

    Sean P. Cornelius

  2. Enginyeria Informàtica i Matemàtiques, Universitat Rovira i Virgili, Tarragona, Tarragona, Spain

    Clara Granell Martorell

  3. Department of Condensed Matter Physics, University of Zaragoza, Zaragoza, Spain

    Jesús Gómez-Gardeñes

  4. JPMorgan Chase & Co (United States), New York, NY, USA

    Bruno Gonçalves

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Krause, R.W., Caimo, A. (2019). Missing Data Augmentation for Bayesian Exponential Random Multi-Graph Models. In: Cornelius, S., Granell Martorell, C., Gómez-Gardeñes, J., Gonçalves, B. (eds) Complex Networks X. CompleNet 2019. Springer Proceedings in Complexity. Springer, Cham. https://doi.org/10.1007/978-3-030-14459-3_5

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