edgecov-ergmTerm-1fb5ef19: Edge covariate

In statnet/ergm: Fit, Simulate and Diagnose Exponential-Family Models for Networks

Edge covariate

Description

This term adds one statistic to the model, equal to the sum of the covariate values for each edge appearing in the network. The edgecov term applies to both directed and undirected networks. For undirected networks the covariates are also assumed to be undirected. The edgecov and dyadcov terms are equivalent for undirected networks.

Usage

# binary: edgecov(x, attrname=NULL)

# valued: edgecov(x, attrname=NULL, form="sum")

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).

form

how to aggregate tie values in a valued ERGM: "sum" (the default) for a statistic of the form \sum_{i,j} x_{i,j} y_{i,j}, where y_{i,j} is the value of dyad (i,j) and x_{i,j} is the term's covariate associated with it; and "nonzero" with the edge considered to be present if its value is not 0. See ergmTerm for more information.

See Also

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

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

statnet/ergm documentation built on Feb. 28, 2025, 7:05 p.m.