ergm

R package ergm: Fit, Simulate and Diagnose Exponential-Family Models for Networks. An integrated set of tools to analyze and simulate networks based on exponential-family random graph models (ERGM). ”ergm” is a part of the ”statnet” suite of packages for network analysis.

Keywords for this software

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References in zbMATH (referenced in 68 articles , 1 standard article )

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  1. Casleton, Emily; Nordman, Daniel J.; Kaiser, Mark S.: Modeling transitivity in local structure graph models (2022)
  2. Alberto Caimo, Lampros Bouranis, Robert Krause, Nial Friel: Statistical Network Analysis with Bergm (2021) arXiv
  3. Bi, Youyi; Qiu, Yunjian; Sha, Zhenghui; Wang, Mingxian; Fu, Yan; Contractor, Noshir; Chen, Wei: Modeling multi-year customers’ considerations and choices in China’s auto market using two-stage bipartite network analysis (2021)
  4. Butts, Carter T.: Phase transitions in the edge/concurrent vertex model (2021)
  5. Eck, Daniel J.; Geyer, Charles J.: Computationally efficient likelihood inference in exponential families when the maximum likelihood estimator does not exist (2021)
  6. Matteo Magnani, Luca Rossi, Obaida Hanteer, Davide Vega: Analysis of Multiplex Social Networks with R (2021) not zbMATH
  7. Qiao, Lei; Han, Dong: CUSUM multi-chart for detecting unknown abrupt changes under finite measure space for network observation sequences (2021)
  8. Yu, Yue; Grazioli, Gianmarc; Phillips, Nolan E.; Butts, Carter T.: Local graph stability in exponential family random graph models (2021)
  9. Caimo, Alberto; Gollini, Isabella: A multilayer exponential random graph modelling approach for weighted networks (2020)
  10. J. Antonio Rivero Ostoic: Algebraic Analysis of Multiple Social Networks with multiplex (2020) not zbMATH
  11. Kaplan, Andee; Kaiser, Mark S.; Lahiri, Soumendra N.; Nordman, Daniel J.: Simulating Markov random fields with a conclique-based Gibbs sampler (2020)
  12. Krivitsky, Pavel N.; Koehly, Laura M.; Marcum, Christopher Steven: Exponential-family random graph models for multi-layer networks (2020)
  13. Lee, Jihui; Li, Gen; Wilson, James D.: Varying-coefficient models for dynamic networks (2020)
  14. Marina Knight, Kathryn Leeming, Guy Nason, Matthew Nunes: Generalized Network Autoregressive Processes and the GNAR Package (2020) not zbMATH
  15. Park, Jaewoo; Haran, Murali: A function emulation approach for doubly intractable distributions (2020)
  16. Schweinberger, Michael; Krivitsky, Pavel N.; Butts, Carter T.; Stewart, Jonathan R.: Exponential-family models of random graphs: inference in finite, super and infinite population scenarios (2020)
  17. Su, Lin; Lu, Wenbin; Song, Rui; Huang, Danyang: Testing and estimation of social network dependence with time to event data (2020)
  18. Tan, Linda S. L.; Friel, Nial: Bayesian variational inference for exponential random graph models (2020)
  19. Waleed Almutiry, Vineetha Warriyar K V, Rob Deardon: Continuous Time Individual-Level Models of Infectious Disease: a Package EpiILMCT (2020) arXiv
  20. Xu Dong, Luis Castro, Nazrul Shaikh: fastnet: An R Package for Fast Simulation and Analysis of Large-Scale Social Networks (2020) not zbMATH

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