Journal article
Maximum likelihood estimation for social network dynamics
- Abstract:
- A model for network panel data is discussed, based on the assumption that the observed data are discrete observations of a continuous-time Markov process on the space of all directed graphs on a given node set, in which changes in tie variables are independent conditional on the current graph. The model for tie changes is parametric and designed for applications to social network analysis, where the network dynamics can be interpreted as being generated by choices made by the social actors represented by the nodes of the graph. An algorithm for calculating the Maximum Likelihood estimator is presented, based on data augmentation and stochastic approximation. An application to an evolving friendship network is given and a small simulation study is presented which suggests that for small data sets the Maximum Likelihood estimator is more efficient than the earlier proposed Method of Moments estimator.
- Publication status:
- Published
Actions
Access Document
- Publisher copy:
- 10.1214/09-AOAS313
Authors
- Journal:
- Annals of Applied Statistics More from this journal
- Volume:
- 4
- Issue:
- 2
- Pages:
- 567-588
- Publication date:
- 2010-11-08
- DOI:
- ISSN:
-
1932-6157
- Keywords:
- Pubs id:
-
pubs:97817
- UUID:
-
uuid:ec80c482-ea0c-4ceb-93ab-088a3960fc66
- Local pid:
-
pubs:97817
- Source identifiers:
-
97817
- Deposit date:
-
2012-12-19
- ARK identifier:
Terms of use
- Copyright date:
- 2010
- Notes:
-
Published in at http://dx.doi.org/10.1214/09-AOAS313 the Annals of
Applied Statistics (http://www.imstat.org/aoas/) by the Institute of
Mathematical Statistics (http://www.imstat.org)
If you are the owner of this record, you can report an update to it here: Report update to this record