Adds a random sociality effect to the model, with normal prior centered around \(0\) and a variance that is estimated. Can only be used on directed networks.
Important: This term works in latentnet's ergmm() only. Using it in ergm() will result in an error.
# binary: rsociality(var=1, var.df=3)# valued: rsociality(var=1, var.df=3)
The scale parameter for the scale-inverse-chi-squared
prior distribution of the sociality effect variance. To set
it in the prior argument to ergmm, use
sociality.var.
The degrees of freedom parameter for the
scale-inverse-chi-squared prior distribution of the sociality effect
variance. To set it in the prior argument to
ergmm, use sociality.var.df.
The following parameters are associated with this term:
socialityNumeric vector of values of each vertex's random sociality effect.
sociality.varRandom sociality effect's variance.
ergmTerm for index of model terms currently visible to the package.
ergm:::.formatTermKeywords("ergmTerm", "rsociality", "subsection")