family_to_trafo_torch

Character-to-transformation mapping function

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

family_to_trafo_torch function

<dl><dt>family</dt>
<dd>character defining the distribution</dd>
<dt>add_const</dt>
<dd>see <code>make_torch_dist</code></dd></dl>

Arguments

Character-to-transformation mapping function — family_to_trafo_torch

<dl>

<dt>family</dt>
<dd>character defining the distribution</dd>


<dt>add_const</dt>
<dd>see <code>make_torch_dist</code></dd>

</dl>

family_to_trafo_torch: Character-to-transformation mapping function

Description

Usage

Value

Arguments