Structure for Organizing Monte Carlo Simulation Designs


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Documentation for package ‘SimDesign’ version 2.15.1

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SimDesign-package Structure for Organizing Monte Carlo Simulation Designs
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
Analyse Compute estimates and statistics
AnalyseIf Perform a test that indicates whether a given 'Analyse()' function should be executed
Attach Attach objects for easier reference
BF_sim Example simulation from Brown and Forsythe (1974)
BF_sim_alternative (Alternative) Example simulation from Brown and Forsythe (1974)
bias Compute (relative/standardized) bias summary statistic
boot_predict Compute prediction estimates for the replication size using bootstrap MSE estimates
Bradley1978 Bradley's (1978) empirical robustness interval
CC Compute congruence coefficient
colSDs Form Column Standard Deviation and Variances
colVars Form Column Standard Deviation and Variances
convertWarnings Wrapper to convert all/specific warning messages to errors
createDesign Create the simulation design object
ECR Compute empirical coverage rates
EDR Compute the empirical detection/rejection rate for Type I errors and Power
ERR Compute the empirical detection/rejection rate for Type I errors and Power
expandDesign Create the simulation design object
Generate Generate data
GenerateIf Perform a test that indicates whether a given 'Generate()' function should be executed
gen_seeds Generate random seeds
getArrayID Get job array ID (e.g., from SLURM or other HPC array distributions)
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
nc Auto-named Concatenation of Vector or List
PBA Probabilistic Bisection Algorithm
plot.PBA Probabilistic Bisection Algorithm
plot.RM Robbins-Monro (1951) stochastic root-finding algorithm
plot.SimSolve One Dimensional Root (Zero) Finding in Simulation Experiments
print.Design Create the simulation design object
print.PBA Probabilistic Bisection Algorithm
print.RM Robbins-Monro (1951) stochastic root-finding algorithm
print.SFA Surrogate Function Approximation via the Generalized Linear Model
print.SimDesign Run a Monte Carlo simulation given conditions and simulation functions
quiet Suppress function messages and Concatenate and Print (cat)
RAB Compute the relative absolute bias of multiple estimators
rbind.SimDesign Combine two separate SimDesign objects by row
RD Compute the relative difference
RE Compute the relative efficiency of multiple estimators
rejectionSampling Rejection sampling (i.e., accept-reject method)
reSummarise Run a summarise step for results that have been saved to the hard drive
rHeadrick Generate non-normal data with Headrick's (2002) 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
RMSD Compute the (normalized) root mean square error
RMSE Compute the (normalized) root mean square error
rmvnorm Generate data with the multivariate normal (i.e., Gaussian) distribution
rmvt Generate data with the multivariate t distribution
RobbinsMonro Robbins-Monro (1951) stochastic root-finding algorithm
RSE Compute the relative standard error ratio
rtruncate Generate a random set of values within a truncated range
runArraySimulation Run a Monte Carlo simulation using array job submissions per condition
runSimulation Run a Monte Carlo simulation given conditions and simulation functions
rValeMaurelli Generate non-normal data with Vale & Maurelli's (1983) method
Serlin2000 Empirical detection robustness method suggested by Serlin (2000)
SFA Surrogate Function Approximation via the Generalized Linear Model
SimAnova Function for decomposing the simulation into ANOVA-based effect sizes
SimCheck Check the status of the simulation's temporary results
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
SimSolve One Dimensional Root (Zero) Finding in Simulation Experiments
Summarise Summarise simulated data using various population comparison statistics
summary.SimDesign Run a Monte Carlo simulation given conditions and simulation functions
summary.SimSolve One Dimensional Root (Zero) Finding in Simulation Experiments