evaluateVarianceFIM

evaluateVarianceFIM: evaluate the variance
evaluateVarianceFIM: evaluate the variance
evaluateVarianceFIM: evaluate the variance

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

evaluateVarianceFIM function

<dl><dt>arm</dt>
<dd>A object of class <code>Arm</code> giving the arm.</dd>
<dt>model</dt>
<dd>A object of class <code>Model</code> giving the model.</dd>
<dt>fim</dt>
<dd>A object of class <code>PopulationFim</code> giving the Fim.</dd></dl>

Arguments

evaluateVarianceFIM: evaluate the variance — evaluateVarianceFIM

<dl>

<dt>arm</dt>
<dd>A object of class <code>Arm</code> giving the arm.</dd>


<dt>model</dt>
<dd>A object of class <code>Model</code> giving the model.</dd>


<dt>fim</dt>
<dd>A object of class <code>PopulationFim</code> giving the Fim.</dd>

</dl>

evaluateVarianceFIM: evaluateVarianceFIM: evaluate the variance

Description

Value

Arguments