Models the effect of a dyadic covariate on the propensity of an ego \(i\) to rank alter \(j\) highly.
# valued: rank.edgecov(x, attrname)either a square matrix of covariates, one for
each possible edge in the network, the name of a network
attribute of covariates, or a network; if the latter, or if the
network attribute named by x is itself a network, optional
argument attrname provides the name of the quantitative edge
attribute to use for covariate values (in this case, missing
edges in x are assigned a covariate value of zero).
ergmTerm for index of model terms currently visible to the package.
ergm:::.formatTermKeywords("ergmTerm", "rank.edgecov", "subsection")