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: |
0.6.0 |
| 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: |
2021-05-21 |
| Author: |
Andrew C. Hooker 
[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
[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 |
| CRAN checks: |
PopED results |