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
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
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).