Introduction to Network Modeling Using Exponential Random Graph Models (ERGM): Theory and an Application Using R-Project
Idioma
EN
Article de revue
Este ítem está publicado en
Computational Economics. 2018, vol. 54, n° 3, p. pp.845-875
Resumen en inglés
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 ...Leer más >
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 papers within economics is however limited. Possible 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 analyse goodness of fit. After reading this paper the reader should be able to start their own analysis.< Leer menos
Palabras clave en inglés
Networks
Exponential random graph model (ERGM)
Innovation networks
p-Star (p*)
Statnet
Tie formation
Centros de investigación