PLNfamily

<p>super class for <code><a rd-options="" href="/link/PLNPCAfamily?package=PLNmodels&version=0.9.5" data-mini-rdoc="PLNmodels::PLNPCAfamily">PLNPCAfamily</a></code> and <code><a rd-options="" href="/link/PLNnetworkfamily?package=PLNmodels&version=0.9.5" data-mini-rdoc="PLNmodels::PLNnetworkfamily">PLNnetworkfamily</a></code></p>
<p>This class comes with a set of methods, some of them being useful for the user:
See the documentation for <code><a rd-options="=getBestModel.PLNnetworkfamily" href="/link/getBestModel?package=PLNmodels&version=0.9.5&to=%3DgetBestModel.PLNnetworkfamily" data-mini-rdoc="=getBestModel.PLNnetworkfamily::getBestModel">getBestModel</a></code>,
<code><a rd-options="=getModel.PLNnetworkfamily" href="/link/getModel?package=PLNmodels&version=0.9.5&to=%3DgetModel.PLNnetworkfamily" data-mini-rdoc="=getModel.PLNnetworkfamily::getModel">getModel</a></code> and  <code><a rd-options="=plot.PLNnetworkfamily" href="/link/plot?package=PLNmodels&version=0.9.5&to=%3Dplot.PLNnetworkfamily" data-mini-rdoc="=plot.PLNnetworkfamily::plot">plot</a></code>.</p>

The Poisson-lognormal model and variants can be used for
a variety of multivariate problems when count data are at play, including
principal component analysis for count data (Chiquet, Mariadassou and Robin,
2018 <doi:10.1214/18-AOAS1177>), discriminant analysis and
network inference (Chiquet, Mariadassou and Robin, 2018 <http://proceedings.mlr.press/v97/chiquet19a.html>).
Implements variational algorithms to fit such models accompanied with a set of
functions for visualization and diagnostic.

Julien Chiquet

PLNmodels

Poisson Lognormal Models

Mahendra Mariadassou

St<c3><a9>phane Robin

PLNfamily function

<p></p><dl class="dl-horizontal">
<dt><code>responses</code></dt><dd><p>the matrix of responses common to every models</p></dd><p></p><p><dt><code>covariates</code></dt><dd><p>the matrix of covariates common to every models</p></dd></p><p><dt><code>offsets</code></dt><dd><p>the matrix of offsets common to every models</p></dd></p><p><dt><code>weights</code></dt><dd><p>the vector of observation weights</p></dd></p><p><dt><code>models</code></dt><dd><p>a list of <code><a rd-options="=PLNnetworkfit" href="/link/PLNnetworkfit?package=PLNmodels&version=0.9.5&to=%3DPLNnetworkfit" data-mini-rdoc="=PLNnetworkfit::PLNnetworkfit">PLNnetworkfit</a></code> object, one per penalty.</p></dd></p><p><dt><code>inception</code></dt><dd><p>a <code><a rd-options="=PLNfit" href="/link/PLNfit?package=PLNmodels&version=0.9.5&to=%3DPLNfit" data-mini-rdoc="=PLNfit::PLNfit">PLNfit</a></code> object, obtained when no sparsifying penalty is applied.</p></dd>
</p></dl><p></p>

Public fields

<p></p><dl class="dl-horizontal">
<dt><code>criteria</code></dt><dd><p>a data frame with the values of some criteria (variational lower bound J, BIC, ICL and R2) for the different models.</p></dd>
</dl><p></p>

Active bindings

<h3>Public methods</h3><p></p><p><ul>
<li><p><a href="/link/PLNfamily%24new()?package=PLNmodels&version=0.9.5" data-mini-rdoc="PLNmodels::PLNfamily$new()"><code>PLNfamily$new()</code></a></p></li>
<li><p><a href="/link/PLNfamily%24postTreatment()?package=PLNmodels&version=0.9.5" data-mini-rdoc="PLNmodels::PLNfamily$postTreatment()"><code>PLNfamily$postTreatment()</code></a></p></li>
<li><p><a href="/link/PLNfamily%24getModel()?package=PLNmodels&version=0.9.5" data-mini-rdoc="PLNmodels::PLNfamily$getModel()"><code>PLNfamily$getModel()</code></a></p></li>
<li><p><a href="/link/PLNfamily%24plot()?package=PLNmodels&version=0.9.5" data-mini-rdoc="PLNmodels::PLNfamily$plot()"><code>PLNfamily$plot()</code></a></p></li>
<li><p><a href="/link/PLNfamily%24show()?package=PLNmodels&version=0.9.5" data-mini-rdoc="PLNmodels::PLNfamily$show()"><code>PLNfamily$show()</code></a></p></li>
<li><p><a href="/link/PLNfamily%24print()?package=PLNmodels&version=0.9.5" data-mini-rdoc="PLNmodels::PLNfamily$print()"><code>PLNfamily$print()</code></a></p></li>
<li><p><a href="/link/PLNfamily%24clone()?package=PLNmodels&version=0.9.5" data-mini-rdoc="PLNmodels::PLNfamily$clone()"><code>PLNfamily$clone()</code></a></p></li>
</ul>
</p><p></p><h3>Method <code>new()</code></h3><p></p><p></p><h3>Usage</h3><p></p><p><pre>PLNfamily$new(responses, covariates, offsets, weights, control)</pre></p><p></p><p></p><h3>Method <code>postTreatment()</code></h3><p></p><p></p><h3>Usage</h3><p></p><p><pre>PLNfamily$postTreatment()</pre></p><p></p><p></p><h3>Method <code>getModel()</code></h3><p></p><p></p><h3>Usage</h3><p></p><p><pre>PLNfamily$getModel(var, index = NULL)</pre></p><p></p><p></p><h3>Method <code>plot()</code></h3><p></p><p></p><h3>Usage</h3><p></p><p><pre>PLNfamily$plot(criteria, annotate = TRUE)</pre></p><p></p><p></p><h3>Method <code>show()</code></h3><p></p><p></p><h3>Usage</h3><p></p><p><pre>PLNfamily$show()</pre></p><p></p><p></p><h3>Method <code>print()</code></h3><p></p><p></p><h3>Usage</h3><p></p><p><pre>PLNfamily$print()</pre></p><p></p><p></p><h3>Method <code>clone()</code></h3><p></p><p>The objects of this class are cloneable with this method.
</p><h3>Usage</h3><p></p><p><pre>PLNfamily$clone(deep = FALSE)</pre></p><p></p><h3>Arguments</h3><p></p><p><dl class="dl-horizontal">
<dt><code>deep</code></dt><dd><p>Whether to make a deep clone.</p></dd>
</dl></p>

Methods

<p>super class for <code><a rd-options='' href='PLNPCAfamily'>PLNPCAfamily</a></code> and <code><a rd-options='' href='PLNnetworkfamily'>PLNnetworkfamily</a></code></p>
<p>This class comes with a set of methods, some of them being useful for the user:
See the documentation for <code><a rd-options='=getBestModel.PLNnetworkfamily' href='getBestModel'>getBestModel</a></code>,
<code><a rd-options='=getModel.PLNnetworkfamily' href='getModel'>getModel</a></code> and  <code><a rd-options='=plot.PLNnetworkfamily' href='plot'>plot</a></code>.</p>

An R6 Class to represent a collection of PLNfit — PLNfamily

<p></p><dl class='dl-horizontal'>
<dt><code>criteria</code></dt><dd><p>a data frame with the values of some criteria (variational lower bound J, BIC, ICL and R2) for the different models.</p></dd>
</dl><p></p>

PLNfamily: An R6 Class to represent a collection of PLNfit

Description

Arguments

Public fields

Active bindings

Methods

Public methods

Method `new()`

Usage

Method `postTreatment()`

Usage

Method `getModel()`

Usage

Method `plot()`

Usage

Method `show()`

Usage

Method `print()`

Usage

Method `clone()`

Usage

Arguments

Description

Arguments

Public fields

Active bindings

Methods

Public methods

Method new()

Usage

Method postTreatment()

Usage

Method getModel()

Usage

Method plot()

Usage

Method show()

Usage

Method print()

Usage

Method clone()

Usage

Arguments

Method `new()`

Method `postTreatment()`

Method `getModel()`

Method `plot()`

Method `show()`

Method `print()`

Method `clone()`