doi:10.1016/j.cmpb.2012.05.005>, and Foracchia et al. (2004) <doi:10.1016/S0169-2607(03)00073-7>.">

PopED: Population (and Individual) Optimal Experimental Design (original) (raw)

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>.

Version: 0.7.0
Depends: R (≥ 2.14)
Imports: ggplot2, MASS, mvtnorm, dplyr (≥ 0.7.0), codetools, stats, utils, magrittr, boot, purrr, stringr, tibble, gtools
Suggests: testthat, Hmisc, nlme, GA, deSolve, Rcpp, shiny, rhandsontable, knitr, rmarkdown, gridExtra, covr, devtools, mrgsolve
Published: 2024-10-07
DOI: 10.32614/CRAN.package.PopED
Author: Andrew C. Hooker ORCID iD [aut, cre, trl, cph], Marco Foracchia [aut] (O-Matrix version), Eric Stroemberg [ctb] (MATLAB version), Martin Fink [ctb] (Streamlining code, added functionality, vignettes), Giulia Lestini [ctb] (Streamlining code, added functionality, vignettes), Sebastian Ueckert ORCID iD [aut] (MATLAB version), Joakim Nyberg [aut] (MATLAB version)
Maintainer: Andrew C. Hooker <andrew.hooker at farmaci.uu.se>
BugReports: https://github.com/andrewhooker/PopED/issues
License: LGPL (≥ 3)
Copyright: 2014-2021 Andrew C. Hooker
URL: https://andrewhooker.github.io/PopED/,https://github.com/andrewhooker/PopED
NeedsCompilation: no
Citation: PopED citation info
Materials: README, NEWS
In views: ExperimentalDesign, MixedModels, Pharmacokinetics
CRAN checks: PopED results

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