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Optimal sequential tests for detection of changes under finite measure space for finite sequences of networks

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  • Lei Qiao
  • Dong Han

Abstract

This paper considers the change-point problem for finite sequences of networks. To avoid the difficulty of computing the normalization coefficient in the models such as Exponential Random Graphical Model (ERGM) and Markov networks, we construct a finite measure space with measure ratio statistics. A new performance measure of detection delay is proposed to detect the changes in distribution of the network data. And under the performance measure we defined, an optimal sequential test is presented. The good performance of the optimal sequential test is illustrated numerically on ERGM and Erdős–Rényi network sequences.

Suggested Citation

  • Lei Qiao & Dong Han, 2022. "Optimal sequential tests for detection of changes under finite measure space for finite sequences of networks," Communications in Statistics - Theory and Methods, Taylor & Francis Journals, vol. 51(19), pages 6585-6600, October.
    • Handle: RePEc:taf:lstaxx:v:51:y:2022:i:19:p:6585-6600
    DOI: 10.1080/03610926.2020.1864824
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