checkValiditySamplingConstraint

checkValiditySamplingConstraint: check if the constraints used for the design optimization are valid.

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

checkValiditySamplingConstraint function

<dl><dt>design</dt>
<dd>An object <code>Design</code> giving the design.</dd></dl>

Arguments

checkValiditySamplingConstraint: check if the constraints used for the design optimization are valid. — checkValiditySamplingConstraint

<dl>

<dt>design</dt>
<dd>An object <code>Design</code> giving the design.</dd>

</dl>

checkValiditySamplingConstraint: checkValiditySamplingConstraint: check if the constraints used for the design optimization are valid.

Description

Value

Arguments