  The simulator is an R package that streamlines the process of performing
simulations by creating a common infrastructure that can be easily used and
reused across projects. Methodological statisticians routinely write
simulations to compare their methods to preexisting ones. While developing
ideas, there is a temptation to write "quick and dirty" simulations to try out
ideas. This approach of rapid prototyping is useful but can sometimes backfire
if bugs are introduced. Using the simulator allows one to remove the "dirty"
without sacrificing the "quick." Coding is quick because the statistician
focuses exclusively on those aspects of the simulation that are specific to the
particular paper being written. Code written with the simulator is succinct,
highly readable, and easily shared with others. The modular nature of
simulations written with the simulator promotes code reusability, which saves
time and facilitates reproducibility. The syntax of the simulator leads to
simulation code that is easily human-readable. Other benefits of using the
simulator include the ability to "step in" to a simulation and change one
aspect without having to rerun the entire simulation from scratch, the
straightforward integration of parallel computing into simulations, and the
ability to rapidly generate plots, tables, and reports with minimal effort.
