get_partial_effect

Return partial effect of one smooth term

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_partial_effect function

<dl><dt>object</dt>
<dd>deepregression object</dd>
<dt>names</dt>
<dd>string; for partial match with smooth term</dd>
<dt>return_matrix</dt>
<dd>logical; whether to return the design matrix or</dd>
<dt>which_param</dt>
<dd>integer; which distribution parameter
the partial effect (<code>FALSE</code>, default)</dd>
<dt>newdata</dt>
<dd>data.frame; new data (optional)</dd>
<dt>...</dt>
<dd>arguments passed to <code>get_weight_by_name</code></dd></dl>

Arguments

Return partial effect of one smooth term — get_partial_effect

<dl>

<dt>object</dt>
<dd>deepregression object</dd>


<dt>names</dt>
<dd>string; for partial match with smooth term</dd>


<dt>return_matrix</dt>
<dd>logical; whether to return the design matrix or</dd>


<dt>which_param</dt>
<dd>integer; which distribution parameter
the partial effect (<code>FALSE</code>, default)</dd>


<dt>newdata</dt>
<dd>data.frame; new data (optional)</dd>


<dt>...</dt>
<dd>arguments passed to <code>get_weight_by_name</code></dd>

</dl>

get_partial_effect: Return partial effect of one smooth term

Description

Usage

Arguments