SimFunctions: Template-based generation of the Generate-Analyse-Summarise functions

Description

This function prints template versions of the required Design and Generate-Analyse-Summarise functions for SimDesign to run simulations. Templated output comes complete with the correct inputs, class of outputs, and optional comments to help with the initial definitions. Use this at the start of your Monte Carlo simulation study. Following the definition of the SimDesign template file please refer to detailed the information in runSimulation for how to edit this template to make a working simulation study.

Usage

SimFunctions(
  filename = NULL,
  dir = getwd(),
  comments = FALSE,
  singlefile = TRUE,
  summarise = TRUE,
  generate = TRUE,
  openFiles = TRUE
)

Arguments

filename

a character vector indicating whether the output should be saved to two respective files containing the simulation design and the functional components, respectively. Using this option is generally the recommended approach when beginning to write a Monte Carlo simulation

dir

the directory to write the files to. Default is the working directory

comments

logical; include helpful comments? Default is FALSE

singlefile

logical; when filename is included, put output in one files? When FALSE the output is saved to two separate files containing the functions and design definitions. The two-file format often makes organization and debugging slightly easier, especially for larger Monte Carlo simulations. Default is TRUE

summarise

include summarise function? Default is TRUE

generate

include generate function? Default is TRUE

openFiles

logical; after files have been generated, open them in your text editor (e.g., if Rstudio is running the scripts will open in a new tab)?

Details

The recommended approach to organizing Monte Carlo simulation files is to first save the template generated by this function to the hard-drive by passing a suitable filename argument (which, if users are interacting with R via the RStudio IDE, will also open the template file after it has been saved). For larger simulations, two separate files could also be used (achieved by passing singlefile = FALSE), and may be easier for debugging/sourcing the simulation code; however, this is a matter of preference and does not change any functionality in the package.

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. 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. 10.1080/10691898.2016.1246953

Examples

Run this code

# NOT RUN {
SimFunctions()
SimFunctions(comments = TRUE) #with helpful comments

# }
# NOT RUN {
# write output to two files (recommended for larger MCSs)
SimFunctions('mysim', singlefile = FALSE)

# write output files to a single file with comments
SimFunctions('mysim', comments = TRUE)
# }
# NOT RUN {
# }