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.

Documentation

Manual: PopED.pdf
Vignette: 1. Introduction to PopED

Maintainer: Andrew C. Hooker <andrew.hooker at farmbio.uu.se>

Author(s): Andrew C. Hooker*, Sebastian Ueckert* (MATLAB version), Marco Foracchia* (O-Matrix version), Joakim Nyberg* (MATLAB version), Eric Stroemberg* (MATLAB version)

Install package and any missing dependencies by running this line in your R console:

install.packages("PopED")

Depends R (>= 2.14)
Imports ggplot2, MASS, mvtnorm, dplyr, codetools, stats, utils
Suggests testthat, Hmisc, nlme, GA, deSolve, shiny, rhandsontable, knitr, rmarkdown
Enhances
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Package PopED
Materials
URL http://poped.sourceforge.net
Task Views ExperimentalDesign
Version 0.3.2
Published 2016-12-12
License LGPL (>= 3)
BugReports https://github.com/andrewhooker/PopED/issues
SystemRequirements
NeedsCompilation no
Citation
CRAN checks PopED check results
Package source PopED_0.3.2.tar.gz