GAMart

This function creates artificial GAM-type <code><a href="/link/data.frame?package=bamlss&version=1.2-2" data-mini-rdoc="bamlss::data.frame">data.frame</a></code>s.
 The function is mainly used for testing purposes.

datasets

Infrastructure for estimating probabilistic distributional regression models in a Bayesian framework.
The distribution parameters may capture location, scale, shape, etc. and every parameter may depend
on complex additive terms (fixed, random, smooth, spatial, etc.) similar to a generalized additive model.
The conceptual and computational framework is introduced in Umlauf, Klein, Zeileis (2019)
<doi:10.1080/10618600.2017.1407325> and the R package in Umlauf, Klein, Simon, Zeileis (2021)
<doi:10.18637/jss.v100.i04>.

Nikolaus Umlauf

bamlss

Bayesian Additive Models for Location, Scale, and Shape (and
Beyond)

Nadja Klein

Achim Zeileis

Meike Koehler

Thorsten Simon

Stanislaus Stadlmann

Alexander Volkmann

GAMart function

<dl> <dt>n</dt>
<dd>The number of observations.</dd> <dt>sd</dt>
<dd>Standard deviation of the normal errors.</dd> <dt>seed</dt>
<dd>Sets the <code>seed</code> to <code>111</code>.</dd> <dt>ti</dt>
<dd>For tensor product interaction term, the type of interaction.</dd></dl>

Arguments

This function creates artificial GAM-type <code><a href='https://rdrr.io/r/base/data.frame.html'>data.frame</a></code>s.
 The function is mainly used for testing purposes.

GAM Artificial Data Set — GAMart

<dl>

 <dt>n</dt>
<dd>The number of observations.</dd>

 <dt>sd</dt>
<dd>Standard deviation of the normal errors.</dd>

 <dt>seed</dt>
<dd>Sets the <code>seed</code> to <code>111</code>.</dd>

 <dt>ti</dt>
<dd>For tensor product interaction term, the type of interaction.</dd>

</dl>

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GAMart: GAM Artificial Data Set

Description

Usage

Arguments

Examples