CRAN/E | PopED

PopED

Population (and Individual) Optimal Experimental Design

Installation

About

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.

Citation PopED citation info
andrewhooker.github.io/PopED/
github.com/andrewhooker/PopED
Copyright 2014-2021 Andrew C. Hooker
Bug report File report

Key Metrics

Version 0.6.0
R ≥ 2.14
Published 2021-05-21 1064 days ago
Needs compilation? no
License LGPL (≥ 3)
CRAN checks PopED results

Downloads

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Maintainer

Maintainer

Andrew C. Hooker

andrew.hooker@farmaci.uu.se

Authors

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)

Material

README
NEWS
Reference manual
Package source

In Views

ExperimentalDesign

Vignettes

Examples
Introduction to PopED

macOS

r-release

arm64

r-oldrel

arm64

r-release

x86_64

r-oldrel

x86_64

Windows

r-devel

x86_64

r-release

x86_64

r-oldrel

x86_64

Old Sources

PopED archive

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

Reverse Imports

ncappc