PSOAlgorithm-class

PSOAlgorithm

The class "PSOAlgorithm" implements the PSO algorithm.

Evaluate or optimize designs for nonlinear mixed effects models using the Fisher Information matrix. Methods used in the package refer to
Mentré F, Mallet A, Baccar D (1997) <doi:10.1093/biomet/84.2.429>,
Retout S, Comets E, Samson A, Mentré F (2007) <doi:10.1002/sim.2910>,
Bazzoli C, Retout S, Mentré F (2009) <doi:10.1002/sim.3573>,
Le Nagard H, Chao L, Tenaillon O (2011) <doi:10.1186/1471-2148-11-326>,
Combes FP, Retout S, Frey N, Mentré F (2013) <doi:10.1007/s11095-013-1079-3> and
Seurat J, Tang Y, Mentré F, Nguyen TT (2021) <doi:10.1016/j.cmpb.2021.106126>.

Romain Leroux

PFIM

Population Fisher Information Matrix

France Mentré

Jérémy Seurat

Lucie Fayette

Emmanuelle Comets

Sylvie Retout

PSOAlgorithm-class function

Objects form the class <code>PSOAlgorithm</code> can be created by calls of the form <code>PSOAlgorithm(...)</code> where
(...) are the parameters for the <code>PSOAlgorithm</code> objects.

Objects from the class <code>PSOAlgorithm</code>

<dl>
 <dt><code>maxIteration</code>:</dt>
<dd>A numeric giving the maximum of iterations.</dd> <dt><code>populationSize</code>:</dt>
<dd>A numeric giving the population size.</dd> <dt><code>seed</code>:</dt>
<dd>A numeric giving the seed.</dd> <dt><code>personalLearningCoefficient</code>:</dt>
<dd>A numeric giving the personal learning coefficient.</dd> <dt><code>globalLearningCoefficient</code>:</dt>
<dd>A numeric giving the global learning coefficient.</dd> <dt><code>showProcess</code>:</dt>
<dd>A boolean to show or not the process.</dd> <dt><code>optimalDesign</code>:</dt>
<dd>A <code>Design</code> object giving the optimal design.</dd> <dt><code>iterationAndCriteria</code>:</dt>
<dd>A list giving the optimal criteria at each iteration.</dd> 
</dl>

Slots for <code>PSOAlgorithm</code> objects

Class "PSOAlgorithm" — PSOAlgorithm-class

Objects form the class <code>PSOAlgorithm</code> can be created by calls of the form <code>PSOAlgorithm(...)</code> where
(...) are the parameters for the <code>PSOAlgorithm</code> objects.

<dl>
 <dt><code>maxIteration</code>:</dt>
<dd>A numeric giving the maximum of iterations.</dd>

 <dt><code>populationSize</code>:</dt>
<dd>A numeric giving the population size.</dd>

 <dt><code>seed</code>:</dt>
<dd>A numeric giving the seed.</dd>

 <dt><code>personalLearningCoefficient</code>:</dt>
<dd>A numeric giving the personal learning coefficient.</dd>

 <dt><code>globalLearningCoefficient</code>:</dt>
<dd>A numeric giving the global learning coefficient.</dd>

 <dt><code>showProcess</code>:</dt>
<dd>A boolean to show or not the process.</dd>

 <dt><code>optimalDesign</code>:</dt>
<dd>A <code>Design</code> object giving the optimal design.</dd>

 <dt><code>iterationAndCriteria</code>:</dt>
<dd>A list giving the optimal criteria at each iteration.</dd>

 
</dl>

PSOAlgorithm-class: Class "PSOAlgorithm"

Description

Arguments

Objects from the class <code>PSOAlgorithm</code>

Slots for <code>PSOAlgorithm</code> objects