orthog_P

Function to compute adjusted penalty when orthogonalizing

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

orthog_P function

<dl><dt>P</dt>
<dd>matrix; original penalty matrix</dd>
<dt>Z</dt>
<dd>matrix; constraint matrix</dd></dl>

Arguments

Function to compute adjusted penalty when orthogonalizing — orthog_P

<dl>

<dt>P</dt>
<dd>matrix; original penalty matrix</dd>


<dt>Z</dt>
<dd>matrix; constraint matrix</dd>

</dl>

orthog_P: Function to compute adjusted penalty when orthogonalizing

Description

Usage

Value

Arguments