Glossary
- Actors:
-
Nodes of the network graph
- Behavior:
-
Changing characteristics of actors
- Covariates:
-
Variables which can depend on the actors (actor covariates) or on pairs of actors (dyadic covariates). They are considered “exogenous” variables in the sense that they are not determined by the stochastic process underlying the model
- Dyad:
-
Pair of actors of the network
- Dyadic Indicator:
-
Binary variable indicating the presence or absence of a tie between two actors
- Effects:
-
Specifications of the objective function
- Longitudinal Networks:
-
Repeated measures of networks over time
- Markov Chain:
-
Stochastic process where the probability of future states given the present state does not depend on past states
- Method of Moments:
-
Statistical estimation method consisting of equating sample moments of a distribution with unobserved theoretic moments in order to get an approximation to the solutions of the likelihood...
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Acknowledgments
Nial Friel’s research was supported by a Science Foundation Ireland Research Frontiers Program grant, 09/RFP/MTH2199.
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Caimo, A., Friel, N. (2016). Actor-Based Models for Longitudinal Networks. In: Alhajj, R., Rokne, J. (eds) Encyclopedia of Social Network Analysis and Mining. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-7163-9_166-1
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DOI: https://doi.org/10.1007/978-1-4614-7163-9_166-1
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