EvaluateErrorModelDerivatives

Evaluate the error model derivatives.

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

EvaluateErrorModelDerivatives function

<dl><dt>object</dt>
<dd>An object from the class ModelError.</dd>
<dt>evaluationOutcome</dt>
<dd>A list giving the results of the model evaluation.</dd></dl>

Arguments

Evaluate the error model derivatives. — EvaluateErrorModelDerivatives

<dl>

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


<dt>evaluationOutcome</dt>
<dd>A list giving the results of the model evaluation.</dd>

</dl>

EvaluateErrorModelDerivatives: Evaluate the error model derivatives.

Description

Usage

Value

Arguments