Structure for Organizing Monte Carlo Simulation Designs

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Documentation for package ‘SimDesign’ version 2.14

• DESCRIPTION file.
• User guides, package vignettes and other documentation.
• Package NEWS.

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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
Generate	Generate data
GenerateIf	Perform a test that indicates whether a given 'Generate()' function should be executed
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 a data.frame of 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
runSimulation	Run a Monte Carlo simulation given a data.frame of 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 a data.frame of conditions and simulation functions
summary.SimSolve	One Dimensional Root (Zero) Finding in Simulation Experiments