The DOI matches its Crossref record; 47 of the 47 references it cites were found in a registry or an index.
Exponential-family random graph models for valued networks
Open accessAbstract
Exponential-family random graph models (ERGMs) provide a principled and flexible way to model and simulate features common in social networks, such as propensities for homophily, mutuality, and friend-of-a-friend triad closure, through choice of model terms (sufficient statistics). However, those ERGMs modeling the more complex features have, to date, been limited to binary data: presence or absence of ties. Thus, analysis of valued networks, such as those where counts, measurements, or ranks are observed, has necessitated dichotomizing them, losing information and introducing biases. In this work, we generalize ERGMs to valued networks. Focusing on modeling counts, we formulate an ERGM for networks whose ties are counts and discuss issues that arise when moving beyond the binary case. We introduce model terms that generalize and model common social network features for such data and apply these methods to a network dataset whose values are counts of interactions.
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Cites
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Robbins, H., & Monro, S. (1951) · The Annals of Mathematical Statistics · doi:10.1214/aoms/1177729586 · Cited by 9,643
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Cited by
Configuring Random Graph Models with Fixed Degree Sequences
Fosdick, B. K., Larremore, D. B., Nishimura, J., & Ugander, J. (2018) · SIAM Review · doi:10.1137/16m1087175 · Cited by 246
Regime shifts in the anthropocene: drivers, risks, and resilience
Rocha, J. C., Peterson, G. D., & Biggs, R. (2015) · PLOS ONE · doi:10.1371/journal.pone.0134639 · Cited by 181
Metadata
- Authors
- Krivitsky, P. N.
- Venue
- Electronic Journal of Statistics
- Publisher
- Institute of Mathematical Statistics
- Published
- 2012-01-01
- Volume
- 6
- Issue
- none
- Pages
- 1100-1128
- ISSN
- 1935-7524 (ISSN-L)
- OpenAlex
- W2024818197
- Cited by
- 295
- References
- 47
- FWCI
- 10.46
- Type
- journal article
- Language
- en
- Open access
- gold
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