stddev

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

stddev function

<dl><dt>x</dt>
<dd>object</dd>
<dt>...</dt>
<dd>further arguments passed to the class-specific function</dd></dl>

Arguments

Generic sd function — stddev

<dl>

<dt>x</dt>
<dd>object</dd>


<dt>...</dt>
<dd>further arguments passed to the class-specific function</dd>

</dl>

Generic sd function

stddev: Generic sd function

Description

Usage

Arguments