sendercov-ergmTerm

InitErgmTerm.sendercov

Deprecated for networks without self-loops. Use
<code>nodeocov-ergmTerm</code>,
<code>nodeofactor-ergmTerm</code>,
<code>nodecov-ergmTerm</code> or
<code>nodefactor-ergmTerm</code> instead.
If the attribute is numeric, this term adds one covariate to the
model equaling <code>attrname(i)</code>. If the attribute is not
numeric or <code>force.factor==TRUE</code>, this term adds \(p-1\)
covariates to the model, where \(p\) is the number of unique
values of <code>attrname</code>. The \(k\)th such covariate has the
value <code>attrname(i) == value(k+1)</code>, where <code>value(k)</code> is
the \(k\)th smallest unique value of the <code>attrname</code>
attribute. This term only makes sense if the network is directed.
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

sendercov-ergmTerm function

<dl><dt>attrname</dt>
<dd>a character string giving the name of an attribute
in the network's vertex attribute list.</dd>
<dt>force.factor</dt>
<dd>logical, indicating if <code>attrname</code>'s value
should be interpreted as categorical even if numeric.</dd>
<dt>mean, var</dt>
<dd>prior mean and variance.</dd></dl>

Arguments

Deprecated for networks without self-loops. Use
<code>nodeocov-ergmTerm</code>,
<code>nodeofactor-ergmTerm</code>,
<code>nodecov-ergmTerm</code> or
<code>nodefactor-ergmTerm</code> instead.
If the attribute is numeric, this term adds one covariate to the
model equaling <code>attrname(i)</code>. If the attribute is not
numeric or <code>force.factor==TRUE</code>, this term adds \(p-1\)
covariates to the model, where \(p\) is the number of unique
values of <code>attrname</code>. The \(k\)th such covariate has the
value <code>attrname(i) == value(k+1)</code>, where <code>value(k)</code> is
the \(k\)th smallest unique value of the <code>attrname</code>
attribute. This term only makes sense if the network is directed.
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.

Sender covariate effect — sendercov-ergmTerm

<dl>

<dt>attrname</dt>
<dd>a character string giving the name of an attribute
in the network's vertex attribute list.</dd>


<dt>force.factor</dt>
<dd>logical, indicating if <code>attrname</code>'s value
should be interpreted as categorical even if numeric.</dd>


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

</dl>

sendercov-ergmTerm: Sender covariate effect

Description

Usage

Arguments

See Also