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 39 articles , 1 standard article )

Showing results 1 to 20 of 39.
Sorted by year (citations)

1 2 next

  1. Bouranis, Lampros; Friel, Nial; Maire, Florian: Model comparison for Gibbs random fields using noisy reversible jump Markov chain Monte Carlo (2018)
  2. Chris Groendyke; David Welch: epinet: An R Package to Analyze Epidemics Spread across Contact Networks (2018)
  3. DeMuse, Ryan; Larcomb, Danielle; Yin, Mei: Phase transitions in edge-weighted exponential random graphs: near-degeneracy and universality (2018)
  4. Durante, Daniele; Dunson, David B.: Bayesian inference and testing of group differences in brain networks (2018)
  5. Huang, Danyang; Guan, Guoyu; Zhou, Jing; Wang, Hansheng: Network-based naive Bayes model for social network (2018)
  6. Jiang, Bai; Wu, Tung-Yu; Jin, Yifan; Wong, Wing H.: Convergence of contrastive divergence algorithm in exponential family (2018)
  7. Michael Schweinberger; Pamela Luna: hergm: Hierarchical Exponential-Family Random Graph Models (2018)
  8. Nath, Madhurima; Ren, Yihui; Khorramzadeh, Yasamin; Eubank, Stephen: Determining whether a class of random graphs is consistent with an observed contact network (2018)
  9. Park, Jaewoo; Haran, Murali: Bayesian inference in the presence of intractable normalizing functions (2018)
  10. Philip Leifeld; Skyler Cranmer; Bruce Desmarais: Temporal Exponential Random Graph Models with btergm: Estimation and Bootstrap Confidence Intervals (2018)
  11. Samuel Jenness; Steven Goodreau; Martina Morris: EpiModel: An R Package for Mathematical Modeling of Infectious Disease over Networks (2018)
  12. Kolaczyk, Eric D.: Topics at the frontier of statistics and network analysis. (Re)Visiting the foundations (2017)
  13. Krivitsky, Pavel N.: Using contrastive divergence to seed Monte Carlo MLE for exponential-family random graph models (2017)
  14. Zhou, Jing; Huang, DanYang; Wang, HanSheng: A dynamic logistic regression for network link prediction (2017)
  15. Butts, Carter T.: On the equivalence of the edge/isolate and edge/concurrent tie ERGM families, and their extensions (2016)
  16. Byshkin, Maksym; Stivala, Alex; Mira, Antonietta; Krause, Rolf; Robins, Garry; Lomi, Alessandro: Auxiliary parameter MCMC for exponential random graph models (2016)
  17. Caimo, Alberto; Mira, Antonietta: Efficient computational strategies for doubly intractable problems with applications to Bayesian social networks (2015)
  18. James D. Wilson, Matthew J. Denny, Shankar Bhamidi, Skyler Cranmer, Bruce Desmarais: Stochastic Weighted Graphs: Flexible Model Specification and Simulation (2015) arXiv
  19. Krivitsky, Pavel N.; Kolaczyk, Eric D.: On the question of effective sample size in network modeling: an asymptotic inquiry (2015)
  20. Luke, Douglas A.: A user’s guide to network analysis in R (2015)

1 2 next