library(ZeligNetwork)
data(friendship)
# Fit the model
z.out <- zelig(per ~ perpower, LF="inverse", model="gamma.net", data=friendship)
#Summarize fitted model
# Set explanatory variables
x.low <- setx(z.out)
x.high <- setx(z.out)
# Simulate quantities of interest
s.out <- sim(z.out, x = x.low, x1 = x.high)
# Summarize simulations
summary(s.out)
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