MissingErnmModel

Creates an ERNM likelihood model with missing data

Estimation of fully and partially observed Exponential-Family Random Network Models (ERNM). Exponential-family Random Graph Models (ERGM) and Gibbs Fields are special cases of ERNMs and can also be estimated with the package. Please cite Fellows and Handcock (2012), "Exponential-family Random Network Models" available at <doi:10.48550/arXiv.1208.0121>.

Duncan Clark

ernm

Exponential-Family Random Network Models

Ian Fellows

MissingErnmModel function

<dl><dt>observedSampler</dt>
<dd>a C++ sampler</dd>
<dt>unobservedSampler</dt>
<dd>a C++ sampler conditional upon the observed values</dd>
<dt>...</dt>
<dd>additional parameters for the log likelihood</dd></dl>

Arguments

Creates an ERNM likelihood model with missing data — MissingErnmModel

<dl>

<dt>observedSampler</dt>
<dd>a C++ sampler</dd>


<dt>unobservedSampler</dt>
<dd>a C++ sampler conditional upon the observed values</dd>


<dt>...</dt>
<dd>additional parameters for the log likelihood</dd>

</dl>

MissingErnmModel: Creates an ERNM likelihood model with missing data

Description

Usage

Value

Arguments