predict_gam_handler

Handler for prediction with gam terms

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

predict_gam_handler function

<dl><dt>object</dt>
<dd>sterm</dd>
<dt>newdata</dt>
<dd>data.frame or list</dd></dl>

Arguments

Handler for prediction with gam terms — predict_gam_handler

<dl>

<dt>object</dt>
<dd>sterm</dd>


<dt>newdata</dt>
<dd>data.frame or list</dd>

</dl>

predict_gam_handler: Handler for prediction with gam terms

Description

Usage

Arguments