Abstract for: System Dynamics Modeling with R

Predicting the spread of an infectious disease, estimating population growth, and assessing the capacity of health services to cope with demographic change are all important societal challenges that can benefit from the application of computer simulation. System dynamics is a powerful simulation approach that enables analysts to build simulation models of social systems, with a view to enhancing decision making. R is a flexible programming language designed to enable the best and most thorough exploration of data possible, and has an extensive set of open source libraries that can support decision analysis. This includes the deSolve library which supports numerical integration. For system dynamics practitioners, R provides benefits including: a comprehensive set of statistical and optimization functions that can be used to analyze and calibrate simulation output; a powerful visualization library that can be used to represent the behavior space of system dynamics models, and, support for multi-method approaches to solving complex problems. This workshop will provide a short introduction to R, and will be in two parts. Part I will provide an introduction to R, focusing on vectors, functions and data frames. Part II will introduce the deSolve package, and show how small system dynamics models can be implemented.