layer_dense_module

Function to create custom nn_linear module to overwrite reset_parameters

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

layer_dense_module function

<dl><dt>kernel_initializer</dt>
<dd>string; initializer used to reset_parameters</dd></dl>

Arguments

Function to create custom nn_linear module to overwrite reset_parameters — layer_dense_module

<dl>

<dt>kernel_initializer</dt>
<dd>string; initializer used to reset_parameters</dd>

</dl>

layer_dense_module: Function to create custom nn_linear module to overwrite reset_parameters

Description

Usage

Value

Arguments