rankedgecov-ergmTerm-5905bc22: Dyadic covariates

In ergm.rank: Fit, Simulate and Diagnose Exponential-Family Models for Rank-Order Relational Data

Dyadic covariates

Description

Models the effect of a dyadic covariate on the propensity of an ego i to rank alter j highly.

Usage

# valued: rank.edgecov(x, attrname)

Arguments

x, attrname

a specification for the dyadic covariate: either one of the following, or the name of a network attribute containing one of the following: a covariate matrix with dimensions n \times n for unipartite networks and b \times (n-b) for bipartite networks; attrname, if given, is used to construct the term name. a network object with the same size and bipartitedness as LHS; attrname, if given, 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).

See Also

ergmTerm for index of model terms currently visible to the package.

\Sexpr[results=rd,stage=render]{ergm:::.formatTermKeywords("ergmTerm", "rank.edgecov", "subsection")}

ergm.rank documentation built on Sept. 11, 2025, 9:09 a.m.