median_hilow_poped

Created for back compatibility with older versions of ggplot, and so that 
PopED does not have to load ggplot when started.

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

median_hilow_poped function

<dl><dt>x</dt>
<dd>A numeric vector</dd>
<dt>...</dt>
<dd>Additional arguments passed to Hmisc's smedian.hilow function or 
ggplot2's median_hilow function, depending on your version of ggplot.</dd></dl>

Arguments

Wrap summary functions from Hmisc and ggplot to work with stat_summary in ggplot — median_hilow_poped

<dl>

<dt>x</dt>
<dd>A numeric vector</dd>


<dt>...</dt>
<dd>Additional arguments passed to Hmisc's smedian.hilow function or 
ggplot2's median_hilow function, depending on your version of ggplot.</dd>

</dl>

median_hilow_poped: Wrap summary functions from Hmisc and ggplot to work with stat_summary in ggplot

Description

Usage

Arguments