coef.drEnsemble

Method for extracting ensemble coefficient estimates

Allows for the specification of semi-structured deep distributional regression models which are fitted in a neural network as
proposed by Ruegamer et al. (2023) <doi:10.18637/jss.v105.i02>.
Predictors can be modeled using structured (penalized) linear effects, structured non-linear effects or using an unstructured deep network model.

David Ruegamer

deepregression

Fitting Deep Distributional Regression

Christopher Marquardt

Laetitia Frost

Florian Pfisterer

Philipp Baumann

Chris Kolb

Lucas Kook

coef.drEnsemble function

<dl><dt>object</dt>
<dd>object of class <code>"drEnsemble"</code></dd>
<dt>which_param</dt>
<dd>integer, indicating for which distribution parameter
coefficients should be returned (default is first parameter)</dd>
<dt>type</dt>
<dd>either NULL (all types of coefficients are returned),
"linear" for linear coefficients or "smooth" for coefficients of 
smooth terms</dd>
<dt>...</dt>
<dd>further arguments supplied to <code>coef.deepregression</code></dd></dl>

Arguments

Method for extracting ensemble coefficient estimates — coef.drEnsemble

<dl>

<dt>object</dt>
<dd>object of class <code>"drEnsemble"</code></dd>


<dt>which_param</dt>
<dd>integer, indicating for which distribution parameter
coefficients should be returned (default is first parameter)</dd>


<dt>type</dt>
<dd>either NULL (all types of coefficients are returned),
"linear" for linear coefficients or "smooth" for coefficients of 
smooth terms</dd>


<dt>...</dt>
<dd>further arguments supplied to <code>coef.deepregression</code></dd>

</dl>

coef.drEnsemble: Method for extracting ensemble coefficient estimates

Description

Usage

Value

Arguments