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.

References in zbMATH (referenced in 56 articles , 1 standard article )

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  1. Alberto Caimo, Lampros Bouranis, Robert Krause, Nial Friel: Statistical Network Analysis with Bergm (2021) arXiv
  2. Eck, Daniel J.; Geyer, Charles J.: Computationally efficient likelihood inference in exponential families when the maximum likelihood estimator does not exist (2021)
  3. Yu, Yue; Grazioli, Gianmarc; Phillips, Nolan E.; Butts, Carter T.: Local graph stability in exponential family random graph models (2021)
  4. Caimo, Alberto; Gollini, Isabella: A multilayer exponential random graph modelling approach for weighted networks (2020)
  5. J. Antonio Rivero Ostoic: Algebraic Analysis of Multiple Social Networks with multiplex (2020) not zbMATH
  6. Krivitsky, Pavel N.; Koehly, Laura M.; Marcum, Christopher Steven: Exponential-family random graph models for multi-layer networks (2020)
  7. Lee, Jihui; Li, Gen; Wilson, James D.: Varying-coefficient models for dynamic networks (2020)
  8. Marina Knight, Kathryn Leeming, Guy Nason, Matthew Nunes: Generalized Network Autoregressive Processes and the GNAR Package (2020) not zbMATH
  9. 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)
  10. Su, Lin; Lu, Wenbin; Song, Rui; Huang, Danyang: Testing and estimation of social network dependence with time to event data (2020)
  11. Waleed Almutiry, Vineetha Warriyar K V, Rob Deardon: Continuous Time Individual-Level Models of Infectious Disease: a Package EpiILMCT (2020) arXiv
  12. Xu Dong, Luis Castro, Nazrul Shaikh: fastnet: An R Package for Fast Simulation and Analysis of Large-Scale Social Networks (2020) not zbMATH
  13. Bauer, Verena; Fürlinger, Karl; Kauermann, Göran: A note on parallel sampling in Markov graphs (2019)
  14. Julien Chiquet, Pierre Barbillon, Timothée Tabouy: missSBM: An R Package for Handling Missing Values in the Stochastic Block Model (2019) arXiv
  15. Lyubchich, Vyacheslav; Woodland, Ryan J.: Using isotope composition and other node attributes to predict edges in fish trophic networks (2019)
  16. Bouranis, Lampros; Friel, Nial; Maire, Florian: Model comparison for Gibbs random fields using noisy reversible jump Markov chain Monte Carlo (2018)
  17. Chris Groendyke; David Welch: epinet: An R Package to Analyze Epidemics Spread across Contact Networks (2018) not zbMATH
  18. DeMuse, Ryan; Larcomb, Danielle; Yin, Mei: Phase transitions in edge-weighted exponential random graphs: near-degeneracy and universality (2018)
  19. Durante, Daniele; Dunson, David B.: Bayesian inference and testing of group differences in brain networks (2018)
  20. Griffin, Maryclare; Gile, Krista J.; Fredricksen-Goldsen, Karen I.; Handcock, Mark S.; Erosheva, Elena A.: A simulation-based framework for assessing the feasibility of respondent-driven sampling for estimating characteristics in populations of lesbian, gay and bisexual older adults (2018)

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