Description

Structure for Organizing Monte Carlo Simulation Designs

Details

Provides tools to help organize Monte Carlo simulations in R. The package controls the structure and back-end of Monte Carlo simulations by utilizing a general generate-analyse-summarise strategy. The functions provided control common simulation issues such as re-simulating non-convergent results, support parallel back-end and MPI distributed computations, save and restore temporary files, aggregate results across independent nodes, and provide native support for debugging. The primary function for organizing the simulations is runSimulation. For an in-depth tutorial of the package please refer to Chalmers and Adkins (2020; doi: 10.20982/tqmp.16.4.p248). For an earlier didactic presentation of the package users can refer to Sigal and Chalmers (2016; doi: 10.1080/10691898.2016.1246953). Finally, see the associated wiki on Github (https://github.com/philchalmers/SimDesign/wiki) for other tutorial material, examples, and applications of SimDesign to real-world simulations.

Author(s)

Phil Chalmers rphilip.chalmers@gmail.com

References

Chalmers, R. P., & Adkins, M. C. (2020). Writing Effective and Reliable Monte Carlo Simulations with the SimDesign Package. The Quantitative Methods for Psychology, 16(4), 248-280. doi: 10.20982/tqmp.16.4.p248

Sigal, M. J., & Chalmers, R. P. (2016). Play it again: Teaching statistics with Monte Carlo simulation. Journal of Statistics Education, 24(3), 136-156. doi: 10.1080/10691898.2016.1246953