An Engine for Running Simulations

A framework for performing simulations such as those common in methodological statistics papers. The design principles of this package are described in greater depth in Bien, J. (2016) "The simulator: An Engine to Streamline Simulations," which is available at <>.

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. The paper The Simulator: An Engine to Streamline Simulations discusses the simulator in greater depth.


The easiest way to install the simulator is by using the devtools R package (if not already installed, open R and type install.packages("devtools")). To install simulator, type


in R. This installs simulator from github.


The Getting Started vignette walks you through setting up your first simulation with the simulator.

The best way to get a sense of how to use the simulator is to look at examples. There are several vignettes that demonstrate how the simulator can be used to conduct simulations for some of the most famous statistical methods.

  1. Lasso vignette: Explains basics, including the magrittr pipe and making plots and tables. Also demonstrates some more advanced features such as writing method extensions (such as refitting the result of the lasso or performing cross-validation).
  2. James-Stein vignette: Shows how to step into specific parts of the simulation for troubleshooting your code.
  3. Elastic net vignette: Shows how we can work with a sequence of methods that are identical except for a parameter that varies
  4. Benjamini-Hochberg vignette: Shows how we can load a preexisting simulation and add more random draws without having to rerun anything. It also shows how one can have multiple simulation objects that point to overlapping sets of results.


Reference manual

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0.2.0 by Jacob Bien, 3 years ago

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Browse source code at

Authors: Jacob Bien [aut, cre]

Documentation:   PDF Manual  

GPL-3 license

Imports methods, graphics, grDevices, stats, utils, magrittr

Suggests digest, ggplot2, knitr, rmarkdown, testthat, glmnet, mvtnorm

See at CRAN