Introduction to network modeling using Exponential Random Graph models (ERGM) - Archive ouverte HAL Access content directly
Preprints, Working Papers, ... Year : 2017

Introduction to network modeling using Exponential Random Graph models (ERGM)

Abstract

Exponential Family Random Graph Models (ERGM) are increasingly used in the study of social networks. These models are build to explain the global structure of a network while allowing inference on tie prediction on a micro level. The number of paper within economics is however limited. Applications for economics are however abundant. The aim of this document is to provide an explanation of the basic mechanics behind the models and provide a sample code (using R and the packages statnet and ergm) to operationalize and interpret results and analyze goodness of fit. After reading this paper the reader should be able to launch their own analysis.
Fichier principal
Vignette du fichier
ergm_V3.pdf (339.25 Ko) Télécharger le fichier
Origin : Files produced by the author(s)
Loading...

Dates and versions

hal-01284994 , version 1 (08-03-2016)
hal-01284994 , version 2 (17-10-2017)

Licence

Copyright

Identifiers

  • HAL Id : hal-01284994 , version 2

Cite

Johannes van Der Pol. Introduction to network modeling using Exponential Random Graph models (ERGM). 2017. ⟨hal-01284994v2⟩

Collections

CNRS GRETHA
881 View
7230 Download

Share

Gmail Facebook X LinkedIn More