This approach is used in the Stochastic Actor-Oriented Model of Snijders (2001 ) and in the Longitudinal Exponential Random Graph Model of Snijders & Koskinen (2013). The first of these is actor-oriented\, i.e.\, tie changes are modelled as choices by actors\, which among their outgoing tie variables to toggle\; the second is t ie-oriented\, i.e.\, tie changes are modelled as t oggles of single tie variables. Both are generaliz ed linear models for the (unobserved) continuous-t ime process\, with all the practical modelling fle xibility of such models. Estimation for panel data is more involved\, requiring a simulation approac h. Estimators have been developed along several li nes\, including Method of Moments\, Generalized Me thod of Moments\, Maximum Likelihood\, and Bayesia n\, and are available in the R package RSiena. Thi s package is widely applied in empirical social ne twork studies in the social sciences.

This presentatio n treats the basic definition of the model and som e of its extensions\, e.g.\, co-evolution of multi variate networks. Some open problems\, from a math ematical and from an applied perspective\, will be mentioned. \; \; \; \;&n bsp\; \; \; \; \; \; \;

- Ruth M. Ripley\, Tom A.B. Snijders\, Zsó\;f
ia Boda\, Andrá\;s Vö\;rö\;s\, and P
aulina Preciado\, 2016.
*Manual for SIENA version 4.0*. Oxford: University of Oxfo rd\, Department of Statistics\; Nuffield College. http://www.stats.ox .ac.uk/siena/ \; \; - <
span>Tom A.B. Snijders\, 2001. The statistical eva
luation of social network dynamics.
*Sociologica l Methodology*\, 31\, 361-395. - <
span>Tom A.B. Snijders and Johan Koskinen\, 2013.
"Longitudinal Models". Chapter 11 (pp. 130-140) in
D. Lusher\, J. Koskinen\, and G. Robins\,
*Expo nential Random Graph Models for Social Networks*\, Cambridge: Cambridge University Press. \; - Tom A.B. Snijders\, Gerhar
d G. van de Bunt\, G. G.\, and Christian E.G. Steg
lich\, 2010. Introduction to actor-based mod
els for network dynamics.
*Social Networks*\, 32\, 44&ndash\;60. \; <
/ul>

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