PopED: Population (and Individual) Optimal Experimental Design

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.

Version: 0.3.2
Depends: R (≥ 2.14)
Imports: ggplot2, MASS, mvtnorm, dplyr, codetools, stats, utils
Suggests: testthat, Hmisc, nlme, GA, deSolve, shiny, rhandsontable, knitr, rmarkdown
Published: 2016-12-12
Author: Andrew C. Hooker [aut, cre, trl, cph], Sebastian Ueckert [aut] (MATLAB version), Marco Foracchia [aut] (O-Matrix version), Joakim Nyberg [aut] (MATLAB version), Eric Stroemberg [ctb] (MATLAB version)
Maintainer: Andrew C. Hooker <andrew.hooker at farmbio.uu.se>
BugReports: https://github.com/andrewhooker/PopED/issues
License: LGPL (≥ 3)
Copyright: 2014-2016 Andrew C. Hooker
URL: http://poped.sourceforge.net
NeedsCompilation: no
Citation: PopED citation info
Materials: README NEWS
In views: ExperimentalDesign
CRAN checks: PopED results


Reference manual: PopED.pdf
Vignettes: 1. Introduction to PopED
Package source: PopED_0.3.2.tar.gz
Windows binaries: r-devel: PopED_0.3.2.zip, r-release: PopED_0.3.2.zip, r-oldrel: PopED_0.3.2.zip
OS X binaries: r-release: PopED_0.3.2.tgz, r-oldrel: PopED_0.3.2.tgz
Old sources: PopED archive


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