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.


References in zbMATH (referenced in 46 articles , 1 standard article )

Showing results 1 to 20 of 46.
Sorted by year (citations)

1 2 3 next

  1. Caimo, Alberto; Gollini, Isabella: A multilayer exponential random graph modelling approach for weighted networks (2020)
  2. J. Antonio Rivero Ostoic: Algebraic Analysis of Multiple Social Networks with multiplex (2020) not zbMATH
  3. Waleed Almutiry, Vineetha Warriyar K V, Rob Deardon: Continuous Time Individual-Level Models of Infectious Disease: a Package EpiILMCT (2020) arXiv
  4. Bauer, Verena; Fürlinger, Karl; Kauermann, Göran: A note on parallel sampling in Markov graphs (2019)
  5. Julien Chiquet, Pierre Barbillon, Timothée Tabouy: missSBM: An R Package for Handling Missing Values in the Stochastic Block Model (2019) arXiv
  6. Lyubchich, Vyacheslav; Woodland, Ryan J.: Using isotope composition and other node attributes to predict edges in fish trophic networks (2019)
  7. Bouranis, Lampros; Friel, Nial; Maire, Florian: Model comparison for Gibbs random fields using noisy reversible jump Markov chain Monte Carlo (2018)
  8. Chris Groendyke; David Welch: epinet: An R Package to Analyze Epidemics Spread across Contact Networks (2018) not zbMATH
  9. DeMuse, Ryan; Larcomb, Danielle; Yin, Mei: Phase transitions in edge-weighted exponential random graphs: near-degeneracy and universality (2018)
  10. Durante, Daniele; Dunson, David B.: Bayesian inference and testing of group differences in brain networks (2018)
  11. 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)
  12. Huang, Danyang; Guan, Guoyu; Zhou, Jing; Wang, Hansheng: Network-based naive Bayes model for social network (2018)
  13. Jiang, Bai; Wu, Tung-Yu; Jin, Yifan; Wong, Wing H.: Convergence of contrastive divergence algorithm in exponential family (2018)
  14. Michael Schweinberger; Pamela Luna: hergm: Hierarchical Exponential-Family Random Graph Models (2018) not zbMATH
  15. Nath, Madhurima; Ren, Yihui; Khorramzadeh, Yasamin; Eubank, Stephen: Determining whether a class of random graphs is consistent with an observed contact network (2018)
  16. Park, Jaewoo; Haran, Murali: Bayesian inference in the presence of intractable normalizing functions (2018)
  17. Philip Leifeld; Skyler Cranmer; Bruce Desmarais: Temporal Exponential Random Graph Models with btergm: Estimation and Bootstrap Confidence Intervals (2018) not zbMATH
  18. Samuel Jenness; Steven Goodreau; Martina Morris: EpiModel: An R Package for Mathematical Modeling of Infectious Disease over Networks (2018) not zbMATH
  19. Kolaczyk, Eric D.: Topics at the frontier of statistics and network analysis. (Re)Visiting the foundations (2017)
  20. Krivitsky, Pavel N.: Using contrastive divergence to seed Monte Carlo MLE for exponential-family random graph models (2017)

1 2 3 next