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SUMMARY:Modeling the dynamics of social networks and continuous actor attr
 ibutes - Nynke Niezink (University of Groningen)
DTSTART:20160825T150000Z
DTEND:20160825T152000Z
UID:TALK67059@talks.cam.ac.uk
CONTACT:INI IT
DESCRIPTION:Co-authors:&nbsp\;<i>Tom Snijders (University of Groningen)</i
 >  &nbsp\;  <br><span><br>Social networks and the characteristics of the a
 ctors who constitute these networks are not static\; they evolve interdepe
 ndently over time. People may befriend others with similar political opini
 ons or change their own opinion based on that of their friends. The stocha
 stic actor-oriented model is used to statistically model such dynamic<a ta
 rget="_blank" rel="nofollow"></a>s. We will present an extension of this m
 odel for continuous dynamic actor characteristics. The method available un
 til now assumed actor characteristics to be measured on an ordinal categor
 ical scale\, which yielded practical limitations for applied researchers. 
 We now model the interdependent dynamics by a stochastic differential equa
 tion for the attribute evolution and a Markov chain model for the network 
 evolution. Although the model is too complicated to calculate likelihoods 
 or estimators in closed form\, the stochastic evolution process can be eas
 ily simulated. Therefore\, we estimate model parameters using the method o
 f moments and the Robbins-Monro algorithm for stochastic approximation. We
  will illustrate the proposed method by a study of the relation between fr
 iendship and obesity\, analyzing body mass index as continuous dynamic act
 or attribute.</span>
LOCATION:Seminar Room 1\, Newton Institute
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