rikardn/poped

Population Experimental Design (PopED) in R

PopED: Population (and individual) Experimental Design in R

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.

There are a number of functions to help you with these tasks. See ?poped for more information.

There are several other examples, as r-scripts, in the "examples" folder in the PopED installation directory located at:

system.file("examples", package="PopED")

The same examples are located in the "inst/examples" directory of this repository.