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 |
as.data.frame.SimDesign |
Run a Monte Carlo simulation given a data.frame of conditions and simulation functions |
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) |
bias |
Compute (relative/standardized) bias summary statistic |
boot_predict |
Compute prediction estimates for the replication size using bootstrap MSE estimates |
ECR |
Compute the empirical coverage rate for Type I errors and Power |
EDR |
Compute the empirical detection rate for Type I errors and Power |
extract_error_seeds |
Run a Monte Carlo simulation given a data.frame of conditions and simulation functions |
extract_results |
Run a Monte Carlo simulation given a data.frame of conditions and simulation functions |
Generate |
Generate data |
head.SimDesign |
Run a Monte Carlo simulation given a data.frame of conditions and simulation functions |
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 |
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) |
RD |
Compute the relative difference |
RE |
Compute the relative efficiency of multiple estimators |
rejectionSampling |
Rejection sampling (i.e., accept-reject method) to draw samples from difficult probability density functions |
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 |
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 |
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) |
SimAnova |
Function for decomposing the simulation into ANOVA-based effect sizes |
SimBoot |
Function to present bootstrap standard errors estimates for Monte Carlo simulation meta-statistics |
SimClean |
Removes/cleans files and folders that have been saved |
SimDesign |
Structure for Organizing Monte Carlo Simulation Designs |
SimFunctions |
Skeleton functions for simulations |
SimResults |
Function to read in saved simulation results |
SimShiny |
Generate a basic Monte Carlo simulation GUI template |
subset.SimDesign |
Subset method for SimDesign objects |
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 |
tail.SimDesign |
Run a Monte Carlo simulation given a data.frame of conditions and simulation functions |