form_control

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

form_control function

<dl><dt>precalculate_gamparts</dt>
<dd>logical; if TRUE (default), additive parts are pre-calculated
and can later be used more efficiently. Set to FALSE only if no smooth effects are in the 
formula(s) and a formula is very large so that extracting all terms takes long or might fail</dd>
<dt>check_form</dt>
<dd>logical; if TRUE (default), the formula is checked in <code>process_terms</code></dd></dl>

Arguments

Options for formula parsing — form_control

<dl>

<dt>precalculate_gamparts</dt>
<dd>logical; if TRUE (default), additive parts are pre-calculated
and can later be used more efficiently. Set to FALSE only if no smooth effects are in the 
formula(s) and a formula is very large so that extracting all terms takes long or might fail</dd>


<dt>check_form</dt>
<dd>logical; if TRUE (default), the formula is checked in <code>process_terms</code></dd>

</dl>

Options for formula parsing

form_control: Options for formula parsing

Description

Usage

Value

Arguments