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SimDesign

Structure for Organizing Monte Carlo Simulation Designs

Provides tools to help safely and efficiently 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. For a pedagogical introduction to the package refer to Sigal and Chalmers (2016) <doi:10.1080/10691898.2016.1246953>, and for an in-depth overview of the package and its design philosophy see Chalmers and Adkins (2020) <doi:10.20982/tqmp.16.4.p248>.

Functions (42)

Analyse

Compute estimates and statistics

Attach

Attach the simulation conditions for easier reference

BF_sim

Example simulation from Brown and Forsythe (1974)

BF_sim_alternative

(Alternative) Example simulation from Brown and Forsythe (1974)

Compute congruence coefficient

ECR

Compute empirical coverage rates

EDR

Compute the empirical detection rate for Type I errors and Power

Generate

Generate data

IRMSE

Compute the integrated root mean-square error

MAE

Compute the mean absolute error

MSRSE

Compute the relative performance behavior of collections of standard errors

RAB

Compute the relative absolute bias of multiple estimators

Compute the relative difference

Compute the relative efficiency of multiple estimators

RMSE

Compute the (normalized) root mean square error

Serlin2000

Empirical detection robustness method suggested by Serlin (2000)

SimAnova

Function for decomposing the simulation into ANOVA-based effect sizes

SimClean

Removes/cleans files and folders that have been saved

SimDesign

Structure for Organizing Monte Carlo Simulation Designs

SimExtract

Function to extract extra information from SimDesign objects

SimFunctions

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

SimResults

Function to read in saved simulation results

SimShiny

Generate a basic Monte Carlo simulation GUI template

Summarise

Summarise simulated data using various population comparison statistics

add_missing

Add missing values to a vector given a MCAR, MAR, or MNAR scheme

aggregate_simulations

Collapse separate simulation files into a single result

bias

Compute (relative/standardized) bias summary statistic

boot_predict

Compute prediction estimates for the replication size using bootstrap MSE estimates

createDesign

Create the simulation Design object

quiet

Suppress function messages and Concatenate and Print (cat)

rHeadrick

Generate non-normal data with Headrick's (2002) method

rValeMaurelli

Generate non-normal data with Vale & Maurelli's (1983) method

rbind.SimDesign

Combine two separate SimDesign objects by row

reSummarise

Run a summarise step for results that have been saved to the hard drive

rejectionSampling

Rejection sampling (i.e., accept-reject method)

rint

Generate integer values within specified range

rinvWishart

Generate data with the inverse Wishart distribution

rmgh

Generate data with the multivariate g-and-h distribution

rmvnorm

Generate data with the multivariate normal (i.e., Gaussian) distribution

rmvt

Generate data with the multivariate t distribution

rtruncate

Generate a random set of values within a truncated range

runSimulation

Run a Monte Carlo simulation given a data.frame of conditions and simulation functions

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

SimDesign

Functions (42)

SimDesign

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