Diagnostics and visualization of point process models for event times on a social network

Jing Wu, Anna L. Smith, Tian Zheng

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

1 Scopus citations


Point process models have been used to analyze interaction event times on a social network, in the hope to provide valuable insights for social science research. In this chapter, the authors aim to propose diagnostic statistics and visualization tools for network event times models, which they develop as extensions of evaluation techniques for univariate point process models. They investigate the proposed techniques using simulated studies and real data. The authors introduce the notation for point processes, network point processes and related models. They focus on time-domain diagnoses by applying the time rescaling theorem and inspecting residual processes. The diagnostic tools for detecting network heterogeneity and network structure in residual processes are developed and demonstrated.

Original languageEnglish
Title of host publicationApplied Modeling Techniques and Data Analysis 1
Subtitle of host publicationComputational Data Analysis Methods and Tools
Number of pages17
ISBN (Electronic)9781119821588
StatePublished - Apr 16 2021

Bibliographical note

Publisher Copyright:
© ISTE Ltd 2021. Published by ISTE Ltd and John Wiley & Sons, Inc.


  • Diagnostic statistics
  • Network event times models
  • Network heterogeneity
  • Point process models
  • Simulated studies
  • Social network
  • Time rescaling theorem
  • Visualization tools

ASJC Scopus subject areas

  • General Economics, Econometrics and Finance
  • General Business, Management and Accounting


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