downsizing_general_design

Function takes a design with potentially empty design 
variables and rescues the design so that a FIM can be calculated using <code>mftot</code>.

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

downsizing_general_design function

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

Arguments

Downsize a general design to a specific design — downsizing_general_design

<dl>

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

</dl>

downsizing_general_design: Downsize a general design to a specific design

Description

Usage

Value

Arguments

See Also