orthog_structured_smooths_Z

Orthogonalize structured term by another matrix

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_structured_smooths_Z function

<dl><dt>S</dt>
<dd>matrix; matrix to orthogonalize</dd>
<dt>L</dt>
<dd>matrix; matrix which defines the projection
and its orthogonal complement, in which <code>S</code> is projected</dd></dl>

Arguments

Orthogonalize structured term by another matrix — orthog_structured_smooths_Z

<dl>

<dt>S</dt>
<dd>matrix; matrix to orthogonalize</dd>


<dt>L</dt>
<dd>matrix; matrix which defines the projection
and its orthogonal complement, in which <code>S</code> is projected</dd>

</dl>

orthog_structured_smooths_Z: Orthogonalize structured term by another matrix

Description

Usage

Value

Arguments