loopcov-ergmTerm {latentnet}

Covariate effect on self-loops

Description

This term adds one covariate to the model, for which x[i,i]=attrname(i) and x[i,j]=0 for i!=j. This term only makes sense if the network has self-loops.

Important: This term works in latentnet's ergmm() only. Using it in ergm() will result in an error.

Usage

# binary: loopcov(attrname, mean=0, var=9)

# valued: loopcov(attrname, mean=0, var=9)

Arguments

attrname

a character string giving the name of a numeric (not categorical) attribute in the network's vertex attribute list.

mean, var

prior mean and variance.

See Also

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

Keywords

None