loopcov-ergmTerm

InitErgmTerm.loopcov

This term adds one covariate to the model, for which
<code>x[i,i]=attrname(i)</code> and <code>x[i,j]=0</code> for <code>i!=j</code>.
This term only makes sense if the network has self-loops.
Important: This term works in <a href="https://CRAN.R-project.org/package=latentnet">latentnet</a>'s <code>ergmm()</code> only. Using it in <code>ergm()</code> will result in an error.

Fit and simulate latent position and cluster models for statistical networks. See Krivitsky and Handcock (2008) <doi:10.18637/jss.v024.i05> and Krivitsky, Handcock, Raftery, and Hoff (2009) <doi:10.1016/j.socnet.2009.04.001>.

Pavel N. Krivitsky

latentnet

Latent Position and Cluster Models for Statistical Networks

Mark S. Handcock

Susan M. Shortreed

Jeremy Tantrum

Peter D. Hoff

Li Wang

Kirk Li

Jake Fisher

Jordan T. Bates

loopcov-ergmTerm function

<dl><dt>attrname</dt>
<dd>a character string giving the name of a numeric
(not categorical) attribute in the network's vertex attribute
list.</dd>
<dt>mean, var</dt>
<dd>prior mean and variance.</dd></dl>

Arguments

This term adds one covariate to the model, for which
<code>x[i,i]=attrname(i)</code> and <code>x[i,j]=0</code> for <code>i!=j</code>.
This term only makes sense if the network has self-loops.
Important: This term works in <a href='https://CRAN.R-project.org/package=latentnet'>latentnet</a>'s <code>ergmm()</code> only. Using it in <code>ergm()</code> will result in an error.

Covariate effect on self-loops — loopcov-ergmTerm

<dl>

<dt>attrname</dt>
<dd>a character string giving the name of a numeric
(not categorical) attribute in the network's vertex attribute
list.</dd>


<dt>mean, var</dt>
<dd>prior mean and variance.</dd>

</dl>

loopcov-ergmTerm: Covariate effect on self-loops

Description

Usage

Arguments

See Also