Population Experimental Design (PopED) in R
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index.md

README.md

PopED: Population (and individual) Experimental Design in R

Travis-CI Build Status AppVeyor Build Status CRAN_Status_Badge codecov.io

PopED computes 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 (FIM).

Installation

You need to have R installed. Download the latest version of R from www.r-project.org. Install PopED in R using one of the following methods:

  • latest stable release -- From CRAN. Write at the R command line:
install.packages("PopED")
  • Latest development version -- from Github. Note that the command below installs the "master" (development) branch; if you want the release branch from Github add ref="release" to the install_github() call. The install_github() approach requires that you build from source, i.e. make and compilers must be installed on your system -- see the R FAQ for your operating system; you may also need to install dependencies manually.
devtools::install_github("andrewhooker/PopED")

Getting started

To get started you need to define

  1. A model.
  2. An initial design (and design space if you want to optimize).
  3. The tasks to perform.

Learn more in this introduction to PopED

Contact

You are welcome to: