fun.amoeba

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

fun.amoeba function

<dl><dt>p</dt>
<dd>input is a matrix p whose ndim+1 rows are ndim-dimensional vectors which are the vertices of the starting simplex.</dd>
<dt>y</dt>
<dd>vector whose components must be pre-initialized to the values of funk evaluated at the ndim+1 vertices (rows) of p.</dd>
<dt>ftol</dt>
<dd>the fractional convergence tolerance to be achieved in the function value.</dd>
<dt>itmax</dt>
<dd>maximal number of iterations.</dd>
<dt>funk</dt>
<dd>multidimensional function to be optimized.</dd>
<dt>outcomes</dt>
<dd>A vector giving the outcomes.</dd>
<dt>data</dt>
<dd>a fixed set of data.</dd>
<dt>showProcess</dt>
<dd>A boolean for showing the process or not.</dd></dl>

Arguments

function fun.amoeba — fun.amoeba

<dl>

<dt>p</dt>
<dd>input is a matrix p whose ndim+1 rows are ndim-dimensional vectors which are the vertices of the starting simplex.</dd>


<dt>y</dt>
<dd>vector whose components must be pre-initialized to the values of funk evaluated at the ndim+1 vertices (rows) of p.</dd>


<dt>ftol</dt>
<dd>the fractional convergence tolerance to be achieved in the function value.</dd>


<dt>itmax</dt>
<dd>maximal number of iterations.</dd>


<dt>funk</dt>
<dd>multidimensional function to be optimized.</dd>


<dt>outcomes</dt>
<dd>A vector giving the outcomes.</dd>


<dt>data</dt>
<dd>a fixed set of data.</dd>


<dt>showProcess</dt>
<dd>A boolean for showing the process or not.</dd>

</dl>

function fun.amoeba

fun.amoeba: function fun.amoeba

Description

Usage

Value

Arguments