plot_cv

Plot CV results from deepregression

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

plot_cv function

<dl><dt>x</dt>
<dd><code>drCV</code> object returned by <code>cv.deepregression</code></dd>
<dt>what</dt>
<dd>character indicating what to plot (currently supported 'loss'
or 'weights')</dd>
<dt>engine</dt>
<dd>character indicating which engine was used to setup the NN</dd>
<dt>...</dt>
<dd>further arguments passed to <code>matplot</code></dd></dl>

Arguments

Plot CV results from deepregression — plot_cv

<dl>

<dt>x</dt>
<dd><code>drCV</code> object returned by <code>cv.deepregression</code></dd>


<dt>what</dt>
<dd>character indicating what to plot (currently supported 'loss'
or 'weights')</dd>


<dt>engine</dt>
<dd>character indicating which engine was used to setup the NN</dd>


<dt>...</dt>
<dd>further arguments passed to <code>matplot</code></dd>

</dl>

plot_cv: Plot CV results from deepregression

Description

Usage

Arguments