get_type_pfc

Function to subset parsed formulas

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

get_type_pfc function

<dl><dt>pfc</dt>
<dd>list of parsed formulas</dd>
<dt>type</dt>
<dd>either NULL (all types of coefficients are returned),
"linear" for linear coefficients or "smooth" for coefficients of</dd></dl>

Arguments

Function to subset parsed formulas — get_type_pfc

<dl>

<dt>pfc</dt>
<dd>list of parsed formulas</dd>


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

</dl>

get_type_pfc: Function to subset parsed formulas

Description

Usage

Arguments