EvaluateVarianceModel

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

EvaluateVarianceModel function

<dl><dt>object</dt>
<dd>An object from the class Model.</dd>
<dt>arm</dt>
<dd>An object from the class Arm.</dd>
<dt>evaluationModel</dt>
<dd>A list giving the outputs of the model evaluation.</dd></dl>

Arguments

Evaluate the variance of a model. — EvaluateVarianceModel

<dl>

<dt>object</dt>
<dd>An object from the class Model.</dd>


<dt>arm</dt>
<dd>An object from the class Arm.</dd>


<dt>evaluationModel</dt>
<dd>A list giving the outputs of the model evaluation.</dd>

</dl>

Evaluate the variance of a model.

EvaluateVarianceModel: Evaluate the variance of a model.

Description

Usage

Value

Arguments