SimDesign: SimExtract – R documentation

Become an expert in R — Interactive courses, Cheat Sheets, certificates and more!

SimExtract

Function to extract extra information from SimDesign objects

Description

Function used to extract any error or warnings messages, the seeds associated with any error or warning messages, and any analysis results that were stored in the final simulation object.

Usage

SimExtract(object, what)

Arguments

object

object returned from runSimulation

what

character indicating what information to extract. Possible inputs include 'errors' to return a tibble object containing counts of any error messages, 'warnings' to return a data.frame object containing counts of any warning messages, 'error_seeds' and 'warning_seeds' to extract the associated .Random.seed values associated with the ERROR/WARNING messages, and 'results' to extract the simulation results if the option store_results was passed to runSimulation. Note that 'warning_seeds' are not stored automatically in simulations and require passing store_warning_seeds = TRUE to runSimulation.

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

Examples

## Not run: 

Generate <- function(condition, fixed_objects = NULL) {
    int <- sample(1:10, 1)
    if(int > 5) warning('GENERATE WARNING: int greater than 5')
    if(int == 1) stop('GENERATE WARNING: integer is 1')
    rnorm(5)
}

Analyse <- function(condition, dat, fixed_objects = NULL) {
    int <- sample(1:10, 1)
    if(int > 5) warning('ANALYSE WARNING: int greater than 5')
    if(int == 1) stop('ANALYSE WARNING: int is 1')
    c(ret = 1)
}

Summarise <- function(condition, results, fixed_objects = NULL) {
    mean(results)
}

res <- runSimulation(replications = 100, seed=1234, verbose=FALSE,
                     generate=Generate, analyse=Analyse, summarise=Summarise)
res

SimExtract(res, what = 'errors')
SimExtract(res, what = 'warnings')
seeds <- SimExtract(res, what = 'error_seeds')
seeds[,1:3]

# replicate a specific error for debugging (type Q to exit debugger)
res <- runSimulation(replications = 100, load_seed=seeds[,1], debug='analyse',
                     generate=Generate, analyse=Analyse, summarise=Summarise)




## End(Not run)

SimDesign

Structure for Organizing Monte Carlo Simulation Designs

v2.3

GPL (>= 2)

Authors

Phil Chalmers [aut, cre] (<https://orcid.org/0000-0001-5332-2810>), Matthew Sigal [ctb], Ogreden Oguzhan [ctb]

Initial release