golden-class

golden

<code>"golden"</code> is a reference class for a golden search scalar optimizer,
 for a parameter within an interval.
<code>golden()</code> is the generator for the <code>"golden"</code>
 class. The optimizer uses reverse communications.

classes

Fit linear and generalized linear mixed-effects models.
The models and their components are represented using S4 classes and
methods.  The core computational algorithms are implemented using the
'Eigen' C++ library for numerical linear algebra and 'RcppEigen' "glue".

Ben Bolker

lme4

Linear Mixed-Effects Models using 'Eigen' and S4

Douglas Bates

Martin Maechler

Steven Walker

Rune Haubo Bojesen Christensen

Henrik Singmann

Bin Dai

Fabian Scheipl

Gabor Grothendieck

Peter Green

John Fox

Alexander Bauer

Pavel N. Krivitsky

Emi Tanaka

Mikael Jagan

golden-class function

<dl> <dt>...</dt>
<dd>(partly optional) arguments passed to
 <code>new()</code> must be named arguments. <code>lower</code> and
 <code>upper</code> are the bounds for the scalar parameter; they must be
 finite.</dd></dl>

Arguments

All reference classes extend and inherit methods from
 <code>"envRefClass"</code>.

Extends

Class "golden" and Generator for Golden Search Optimizer Class — golden-class

<dl>

 <dt>...</dt>
<dd>(partly optional) arguments passed to
 <code>new()</code> must be named arguments. <code>lower</code> and
 <code>upper</code> are the bounds for the scalar parameter; they must be
 finite.</dd>

</dl>

Class <code>"golden"</code> and Generator for Golden Search Optimizer Class

golden-class: Class `"golden"` and Generator for Golden Search Optimizer Class

Description

Usage

Arguments

Extends

Examples