Statistics Surveys

A review of dynamic network models with latent variables

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

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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.

Article information

Source
Statist. Surv., Volume 12 (2018), 105-135.

Dates
Received: November 2017
First available in Project Euclid: 3 September 2018

Permanent link to this document
https://projecteuclid.org/euclid.ssu/1535961690

Digital Object Identifier
doi:10.1214/18-SS121

Mathematical Reviews number (MathSciNet)
MR3850294

Zentralblatt MATH identifier
06932495

Subjects
Primary: 62-02: Research exposition (monographs, survey articles) 62-07: Data analysis
Secondary: 05C90: Applications [See also 68R10, 81Q30, 81T15, 82B20, 82C20, 90C35, 92E10, 94C15]

Keywords
Dynamic networks latent space model stochastic blockmodel latent variable model social network analysis

Rights
Creative Commons Attribution 4.0 International License.

Citation

Kim, Bomin; Lee, Kevin H.; Xue, Lingzhou; Niu, Xiaoyue. A review of dynamic network models with latent variables. Statist. Surv. 12 (2018), 105--135. doi:10.1214/18-SS121. https://projecteuclid.org/euclid.ssu/1535961690


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