plotRSE

Plot the relative standard errors RSE of the model parameters.

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

Hervé Le Nagard

Jérémy Seurat

Tran Bach Nguyen

Caroline Bazzoli

Emmanuelle Comets

Anne Dubois

Cyrielle Dumont

Giulia Lestini

Thi Huyen Tram Nguyen

Thu Thuy Nguyen

Sylvie Retout

plotRSE function

<dl><dt>object</dt>
<dd><code>PFIMProject</code> object.</dd></dl>

Arguments

Plot the relative standard errors RSE of the model parameters. — plotRSE

<dl>

<dt>object</dt>
<dd><code>PFIMProject</code> object.</dd>

</dl>

Plot the relative standard errors RSE of the model parameters.

plotRSE: Plot the relative standard errors RSE of the model parameters.

Description

Usage

Value

Arguments