model_torch

Function to initialize a nn_module
Forward functions works with a list. The entries of the list are the input of 
the subnetworks

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

model_torch function

<dl><dt>submodules_list</dt>
<dd>list; subnetworks</dd></dl>

Arguments

Function to initialize a nn_module
Forward functions works with a list. The entries of the list are the input of 
the subnetworks — model_torch

<dl>

<dt>submodules_list</dt>
<dd>list; subnetworks</dd>

</dl>

model_torch: Function to initialize a nn_module Forward functions works with a list. The entries of the list are the input of the subnetworks

Description

Usage

Value

Arguments