Journal article

Snowball sampling for estimating exponential random graph models for large networks

Alex D Stivala, Johan H Koskinen, David A Rolls, Peng Wang, Garry L Robins

Social Networks | ELSEVIER | Published : 2016

Grants

Awarded by Victorian Life Sciences Computation Initiative (VLSCI) grant on its Peak Computing Facility at the University of Melbourne, an initiative of the Victorian Government, Australia


Awarded by National Science Foundation


Awarded by Leverhulme Trust


Awarded by British Academy/Leverhulme


Funding Acknowledgements

This research was supported by a Victorian Life Sciences Computation Initiative (VLSCI) grant numbers VR0261 and VR0297 on its Peak Computing Facility at the University of Melbourne, an initiative of the Victorian Government, Australia. This work used the Extreme Science and Engineering Discovery Environment (XSEDE), which is supported by National Science Foundation grant number ACI-1053575. Specifically, we used the Gordon Compute Cluster at SDSC under allocation TG-SES140024 "Exponential Random Graph Models for Large Networks: Snowball Sampling and Conditional Estimation using Parallel High Performance Computing". We also used the University of Melbourne ITS High Performance Computing facilities. Johan Koskinen acknowledges financial support through the Leverhulme Trust (RPG-2013-140) and British Academy/Leverhulme (SG121127).