R: Edge covariate by attribute pairing

attrcov-ergmTerm {ergm} | R Documentation

## Edge covariate by attribute pairing

### Description

This term adds one statistic to the model, equal to the sum of the covariate values for each edge appearing in the network, where the covariate value for a given edge is determined by its mixing type on `attr`. Undirected networks are regarded as having undirected mixing, and it is assumed that `mat` is symmetric in that case.

This term can be useful for simulating large networks with many mixing types, where `nodemix` would be slow due to the large number of statistics, and `edgecov` cannot be used because an adjacency matrix would be too big.

### Usage

    # binary: attrcov(attr, mat)

### Arguments

`attr` | quantitative attribute (see Specifying Vertex attributes and Levels (`?nodal_attributes`) for details.)
`mat` | a matrix of covariates with the same dimensions as a mixing matrix for `attr`

### See Also

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

[Package ergm version 4.2.1 Index]