dyadSampling_fit

Class for fitting a dyad sampling
Class for fitting a dyad sampling

When a network is partially observed (here, NAs in the adjacency matrix rather than 1 or 0
due to missing information between node pairs), it is possible to account for the underlying process
that generates those NAs. 'missSBM' adjusts the popular stochastic block model from network data
sampled under various missing data conditions, as described in Tabouy, Barbillon and Chiquet (2019) <doi:10.1080/01621459.2018.1562934>.

Julien Chiquet

missSBM

Handling Missing Data in Stochastic Block Models

Pierre Barbillon

Timoth<c3><a9>e Tabouy

gro<c3><9f>BM team

dyadSampling_fit function

<code><a rd-options="missSBM:networkSampling" href="/link/missSBM%3A%3AnetworkSampling?package=missSBM&version=0.3.0&to=missSBM%3AnetworkSampling" data-mini-rdoc="missSBM:networkSampling::missSBM::networkSampling">missSBM::networkSampling</a></code> -&gt; <code><a rd-options="missSBM:networkSamplingDyads_fit" href="/link/missSBM%3A%3AnetworkSamplingDyads_fit?package=missSBM&version=0.3.0&to=missSBM%3AnetworkSamplingDyads_fit" data-mini-rdoc="missSBM:networkSamplingDyads_fit::missSBM::networkSamplingDyads_fit">missSBM::networkSamplingDyads_fit</a></code> -&gt; <code>dyadSampling_fit</code>

Super classes

<dl class="dl-horizontal">
<dt><code>vExpec</code></dt><dd>variational expectation of the sampling</dd>
</dl>

Active bindings

<h3>Public methods</h3><ul>
<li><a href="/link/dyadSampling_fit%24new()?package=missSBM&version=0.3.0" data-mini-rdoc="missSBM::dyadSampling_fit$new()"><code>dyadSampling_fit$new()</code></a></li>
<li><a href="/link/dyadSampling_fit%24clone()?package=missSBM&version=0.3.0" data-mini-rdoc="missSBM::dyadSampling_fit$clone()"><code>dyadSampling_fit$clone()</code></a></li>
</ul>
<ul>
<li><a href="/link/missSBM%3A%3AnetworkSampling%24print()?package=missSBM&version=0.3.0" data-mini-rdoc="missSBM::missSBM::networkSampling$print()"><code>missSBM::networkSampling$print()</code></a></li>
<li><a href="/link/missSBM%3A%3AnetworkSamplingDyads_fit%24show()?package=missSBM&version=0.3.0" data-mini-rdoc="missSBM::missSBM::networkSamplingDyads_fit$show()"><code>missSBM::networkSamplingDyads_fit$show()</code></a></li>
<li><a href="/link/missSBM%3A%3AnetworkSamplingDyads_fit%24update_imputation()?package=missSBM&version=0.3.0" data-mini-rdoc="missSBM::missSBM::networkSamplingDyads_fit$update_imputation()"><code>missSBM::networkSamplingDyads_fit$update_imputation()</code></a></li>
<li><a href="/link/missSBM%3A%3AnetworkSamplingDyads_fit%24update_parameters()?package=missSBM&version=0.3.0" data-mini-rdoc="missSBM::missSBM::networkSamplingDyads_fit$update_parameters()"><code>missSBM::networkSamplingDyads_fit$update_parameters()</code></a></li>
</ul><h3>Method <code>new()</code></h3>constructor
<h3>Usage</h3><pre>dyadSampling_fit$new(partlyObservedNetwork, ...)</pre><h3>Arguments</h3><dl class="dl-horizontal">
<dt><code>partlyObservedNetwork</code></dt><dd>a object with class partlyObservedNetwork representing the observed data with possibly missing entries</dd></dl><dt><code>...</code></dt><dd>used for compatibility</dd>
<h3>Method <code>clone()</code></h3>The objects of this class are cloneable with this method.
<h3>Usage</h3><pre>dyadSampling_fit$clone(deep = FALSE)</pre><h3>Arguments</h3><dl class="dl-horizontal">
<dt><code>deep</code></dt><dd>Whether to make a deep clone.</dd>
</dl>

Methods

Class for fitting a dyad sampling — dyadSampling_fit

<code><a rd-options='missSBM:networkSampling' href='missSBM::networkSampling'>missSBM::networkSampling</a></code> -&gt; <code><a rd-options='missSBM:networkSamplingDyads_fit' href='missSBM::networkSamplingDyads_fit'>missSBM::networkSamplingDyads_fit</a></code> -&gt; <code>dyadSampling_fit</code>

<dl class='dl-horizontal'>
<dt><code>vExpec</code></dt><dd>variational expectation of the sampling</dd>
</dl>

dyadSampling_fit: Class for fitting a dyad sampling

Description

Arguments

Super classes

Active bindings

Methods

Public methods

Method `new()`

Usage

Arguments

Method `clone()`

Usage

Arguments

Description

Arguments

Super classes

Active bindings

Methods

Public methods

Method new()

Usage

Arguments

Method clone()

Usage

Arguments

Method `new()`

Method `clone()`