extract_norm_group_fim

Extract an individual FIM for each group in a design

internal

Optimal experimental designs for both population and individual
studies based on nonlinear mixed-effect models. Often this is based on a
computation of the Fisher Information Matrix. This package was developed
for pharmacometric problems, and examples and predefined models are available
for these types of systems. The methods are described in Nyberg et al.
(2012) <doi:10.1016/j.cmpb.2012.05.005>, and Foracchia et al. (2004)
<doi:10.1016/S0169-2607(03)00073-7>.

Andrew C. Hooker

PopED

Population (and Individual) Optimal Experimental Design

Marco Foracchia

Eric Stroemberg

Martin Fink

Giulia Lestini

Sebastian Ueckert

Joakim Nyberg

extract_norm_group_fim function

<dl><dt>poped.db</dt>
<dd>A PopED database</dd>
<dt>...</dt>
<dd>Arguments passed to <code>evaluate.fim</code></dd></dl>

Arguments

Extract a normalized group FIM — extract_norm_group_fim

<dl>

<dt>poped.db</dt>
<dd>A PopED database</dd>


<dt>...</dt>
<dd>Arguments passed to <code>evaluate.fim</code></dd>

</dl>

extract_norm_group_fim: Extract a normalized group FIM

Description

Usage

Value

Arguments