Volume 24, 2020
|Page(s)||138 - 147|
|Published online||03 March 2020|
- S. Bhamidi, G. Bresler and A. Sly, Mixing time of exponential random graphs. Ann. Appl. Probab. 21 (2011) 2146–2170. [Google Scholar]
- C.T. Butts, A perfect sampling method for exponential family random graph models. J. Math. Sociol. 42 (2018) 17–36. [Google Scholar]
- A. Cerqueira, D. Fraiman, C.D. Vargas and F. Leonardi, A test of hypotheses for random graph distributions built from EEG data. IEEE Trans. Netw. Sci. Eng. (2017). [Google Scholar]
- S. Chatterjee, P. Diaconis et al., Estimating and understanding exponential random graph models. Ann. Stat. 41 (2013) 2428–2461. [Google Scholar]
- C.J. Geyer and E.A. Thompson, Constrained Monte–Carlo maximum likelihood for dependent data. J. Roy. Stat. Soc. Ser. B (Methodological) 54, (1992) 657–699. [Google Scholar]
- D.A. Levin, Y. Peres and E.L. Wilmer, Markov chains and mixing times. American Mathematical Soc. (2009). [Google Scholar]
- M.E. Newman, D.J. Watts and S.H. Strogatz, Random graph models of social networks. Proc. Natl. Acad. Sci. 99 (2002) 2566–2572. [CrossRef] [Google Scholar]
- J.G. Propp and D.B. Wilson, Exact sampling with coupled markov chains and applications to statistical mechanics. Random Struct. Algor. 9 (1996) 223–252. [CrossRef] [Google Scholar]
- G. Robins, P. Pattison, Y. Kalish and D. Lusher, An introduction to exponential random graph (p*) models for social networks. Social Netw. 29 (2007) 173–191. [CrossRef] [Google Scholar]
- T.A. Snijders, Markov chain Monte Carlo estimation of exponential random graph models. J. Soc. Struct. 3 (2002) 1–40. [Google Scholar]
- D. Strauss and M. Ikeda, seudolikelihood estimation for social networks. J. Am. Stat. Assoc. 85 (1990) 204–212. [Google Scholar]
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.