get_weight_by_name

Function to retrieve the weights of a structured layer

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_weight_by_name function

<dl><dt>mod</dt>
<dd>fitted deepregression object</dd>
<dt>name</dt>
<dd>name of partial effect</dd>
<dt>param_nr</dt>
<dd>distribution parameter number</dd>
<dt>postfixes</dt>
<dd>character (vector) appended to layer name</dd></dl>

Arguments

Function to retrieve the weights of a structured layer — get_weight_by_name

<dl>

<dt>mod</dt>
<dd>fitted deepregression object</dd>


<dt>name</dt>
<dd>name of partial effect</dd>


<dt>param_nr</dt>
<dd>distribution parameter number</dd>


<dt>postfixes</dt>
<dd>character (vector) appended to layer name</dd>

</dl>

get_weight_by_name: Function to retrieve the weights of a structured layer

Description

Usage

Value

Arguments