A review of dynamic network models with latent variables

Bomin Kim, Kevin H. Lee, Lingzhou Xue, Xiaoyue Niu

Research output: Contribution to journalReview article

7 Citations (Scopus)

Abstract

We present a selective review of statistical modeling of dynamic networks. We focus on models with latent variables, specifically, the latent space models and the latent class models (or stochastic blockmodels), which investigate both the observed features and the unobserved structure of networks. We begin with an overview of the static models, and then we introduce the dynamic extensions. For each dynamic model, we also discuss its applications that have been studied in the literature, with the data source listed in Appendix. Based on the review, we summarize a list of open problems and challenges in dynamic network modeling with latent variables.

Original languageEnglish (US)
Pages (from-to)105-135
Number of pages31
JournalStatistics Surveys
Volume12
DOIs
StatePublished - Jan 1 2018

Fingerprint

Dynamic Networks
Latent Variables
Network Model
Dynamic Model
Latent Class Model
Network Modeling
Statistical Modeling
Dynamic Modeling
Open Problems
Model
Review
Latent variables
Network model
Network dynamics
Modeling

All Science Journal Classification (ASJC) codes

  • Statistics and Probability
  • Statistics, Probability and Uncertainty

Cite this

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A review of dynamic network models with latent variables. / Kim, Bomin; Lee, Kevin H.; Xue, Lingzhou; Niu, Xiaoyue.

In: Statistics Surveys, Vol. 12, 01.01.2018, p. 105-135.

Research output: Contribution to journalReview article

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AB - We present a selective review of statistical modeling of dynamic networks. We focus on models with latent variables, specifically, the latent space models and the latent class models (or stochastic blockmodels), which investigate both the observed features and the unobserved structure of networks. We begin with an overview of the static models, and then we introduce the dynamic extensions. For each dynamic model, we also discuss its applications that have been studied in the literature, with the data source listed in Appendix. Based on the review, we summarize a list of open problems and challenges in dynamic network modeling with latent variables.

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