golden-class

golden

(partly optional) arguments passed to
    <code><a rd-options="" href="/link/new?package=lme4&version=1.1-13" data-mini-rdoc="lme4::new">new</a>()</code> must be named arguments.  <code>lower</code> and
    <code>upper</code> are the bounds for the scalar parameter; they must be
    finite.

&#8230;

<code>&quot;golden&quot;</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>&quot;golden&quot;</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

Gabor Grothendieck

Peter Green

golden-class function

All reference classes extend and inherit methods from
  <code>&quot;<a href="/link/?package=lme4&version=1.1-13" data-mini-rdoc="lme4::"></a>&quot;</code>.

Extends

(partly optional) arguments passed to
    <code><a rd-options='' href='new'>new</a>()</code> must be named arguments.  <code>lower</code> and
    <code>upper</code> are the bounds for the scalar parameter; they must be
    finite.

Class  — golden-class

All reference classes extend and inherit methods from
  <code>&quot;<a href='envRefClass'></a>&quot;</code>.

golden-class: Class

Description

Usage

Arguments

Extends

Examples