scale2

The function scales numeric objects to specific ranges.

manip

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

scale2 function

<dl> <dt>x</dt>
<dd>Numeric, vector or matrix.</dd> <dt>lower</dt>
<dd>The upper range.</dd> <dt>upper</dt>
<dd>The lower range.</dd></dl>

Arguments

Scaling Vectors and Matrices — scale2

<dl>

 <dt>x</dt>
<dd>Numeric, vector or matrix.</dd>

 <dt>lower</dt>
<dd>The upper range.</dd>

 <dt>upper</dt>
<dd>The lower range.</dd>

</dl>

scale2: Scaling Vectors and Matrices

Description

Usage

Value

Arguments

Examples