modelbuilder - A package for graphical building and analysis of compartmental simulation models
Note
The package has not seen much attention lately and was never fully completed. It should mostly work, but there are no guarantees. Let me know if something fails.
Description
This R package provides functionality that lets the user build and analyze compartmental simulation models, implemented as ordinary differential equations, stochastic equivalents, or discrete time models. All model building and analysis can be done without writing code. The user can export code for one of the model implementations for further customization.
Getting Started
I assume you have R installed. I also highly recommend to have an IDE like Positron or RStudio, though it’s not required. The package has not yet been submitted to CRAN, therefore it currently needs to be installed from Github. To do so, you need the remotes package. If you don’t have it, install it first. Then, install and get modelbuilder up and running with these commands:
library('remotes') #install this package if you don't have it
install_github('andreashandel/modelbuilder')
library('modelbuilder')
modelbuilder()Next, see the Get Started section for a basic and currently sparse - but hopefully still informative - introduction.
Further information
- We developed two packages that teach the use of compartmental simulation models for use on the population level (DSAIDE package), and individual host/patient level (DSAIRM package). Those packages come with pre-coded simulations and are meant for learning, while modelbuilder lets you build your own models and is geared towards more advanced users.
- I regularly teach courses related to infectious diseases and modeling. Materials covering population level infectious diseases and modeling can be found here, similar materials covering modeling on the within-host, patient level can be found here.
- Contributions to the package are very welcome! If you want to take a deeper look at the package, see this Markdown file which provides further information on the details of the package structure. I’d be excited to receive any contributions from individuals who want to help improve the package. If you plan to make substantial contributions, it might be best to get in touch with me first.
- I send out a monthly newsletter in which (among other things) I announce any noteworthy updates to my R packages. If you want to stay updated, you can sign up here.
Acknowledgements
This R package is developed and maintained by Andreas Handel. A full list of contributors can be found here.
This project was/is partially supported by NIH grants U19AI117891, R01 GM124280 and GM 12480-03S1 and a grant from the University of Georgia’s Center for Teaching and Learning.