regularizedSEMMixedPenalty-class

Provides regularized structural equation modeling
(regularized SEM) with non-smooth penalty functions (e.g., lasso) building
on 'lavaan'. The package is heavily inspired by the
['regsem'](<https://github.com/Rjacobucci/regsem>) and
['lslx'](<https://github.com/psyphh/lslx>) packages.

Jannik H. Orzek

lessSEM

Non-Smooth Regularization for Structural Equation Models

regularizedSEMMixedPenalty-class function

<dl>
<dt><code>penalty</code></dt>
<dd>penalty used (e.g., "lasso")</dd></dl>
<dt><code>tuningParameterConfigurations</code></dt>
<dd>list with settings for the lambda, theta,
and alpha tuning parameters.</dd>
<dt><code>parameters</code></dt>
<dd>data.frame with parameter estimates</dd>
<dt><code>fits</code></dt>
<dd>data.frame with all fit results</dd>
<dt><code>parameterLabels</code></dt>
<dd>character vector with names of all parameters</dd>
<dt><code>weights</code></dt>
<dd>vector with weights given to each of the parameters in the penalty</dd>
<dt><code>regularized</code></dt>
<dd>character vector with names of regularized parameters</dd>
<dt><code>transformations</code></dt>
<dd>if the model has transformations, the transformed parameters
are returned</dd>
<dt><code>internalOptimization</code></dt>
<dd>list of elements used internally</dd>
<dt><code>inputArguments</code></dt>
<dd>list with elements passed by the user to the general</dd>
<dt><code>notes</code></dt>
<dd>internal notes that have come up when fitting the model</dd>

Slots

Class for regularized SEM — regularizedSEMMixedPenalty-class

<dl>
<dt><code>penalty</code></dt>
<dd>penalty used (e.g., "lasso")</dd>


<dt><code>tuningParameterConfigurations</code></dt>
<dd>list with settings for the lambda, theta,
and alpha tuning parameters.</dd>


<dt><code>parameters</code></dt>
<dd>data.frame with parameter estimates</dd>


<dt><code>fits</code></dt>
<dd>data.frame with all fit results</dd>


<dt><code>parameterLabels</code></dt>
<dd>character vector with names of all parameters</dd>


<dt><code>weights</code></dt>
<dd>vector with weights given to each of the parameters in the penalty</dd>


<dt><code>regularized</code></dt>
<dd>character vector with names of regularized parameters</dd>


<dt><code>transformations</code></dt>
<dd>if the model has transformations, the transformed parameters
are returned</dd>


<dt><code>internalOptimization</code></dt>
<dd>list of elements used internally</dd>


<dt><code>inputArguments</code></dt>
<dd>list with elements passed by the user to the general</dd>


<dt><code>notes</code></dt>
<dd>internal notes that have come up when fitting the model</dd>


</dl>

regularizedSEMMixedPenalty-class: Class for regularized SEM

Description

Arguments

Slots