get_help_forward_torch

Helper function to calculate amount of layers
Needed when shared layers are used, because of layers have same names

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_help_forward_torch function

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

Arguments

Helper function to calculate amount of layers
Needed when shared layers are used, because of layers have same names — get_help_forward_torch

<dl>

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

</dl>

get_help_forward_torch: Helper function to calculate amount of layers Needed when shared layers are used, because of layers have same names

Description

Usage

Value

Arguments