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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. 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>.
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Package details |
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| Author | Andrew C. Hooker [aut, cre, trl, cph] (<https://orcid.org/0000-0002-2676-5912>), 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, <https://orcid.org/0000-0002-3712-0255>), Joakim Nyberg [aut] (MATLAB version) |
| Maintainer | Andrew C. Hooker <andrew.hooker@farmaci.uu.se> |
| License | LGPL (>= 3) |
| Version | 0.7.0 |
| URL | https://andrewhooker.github.io/PopED/ https://github.com/andrewhooker/PopED |
| Package repository | View on CRAN |
| Installation |
Install the latest version of this package by entering the following in R:
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