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SimDesign (version 1.1)

Structure for Organizing Monte Carlo Simulation Designs

Description

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.

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Install

install.packages('SimDesign')

Monthly Downloads

7,495

Version

1.1

License

GPL (>= 2)

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Maintainer

Phil Chalmers

Last Published

August 10th, 2016

Functions in SimDesign (1.1)

BF_sim_alternative

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

Summarise simulated data using various population comparison statistics
SimFunctions

Skeleton functions for simulations
MAE

Compute the mean absolute error
RE

Compute the relative efficiency of multiple estimators
SimClean

Removes/cleans files and folders that have been saved
SimAnova

Function for decomposing the simulation into ANOVA-based effect sizes
RMSE

Compute the (normalized) root mean square error
runSimulation

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

Structure for Organizing Monte Carlo Simulation Designs
Analyse

Compute estimates and statistics
Attach

Attach the simulation conditions for easier reference
ECR

Compute the empirical coverage rate for Type I errors and Power
bias

Compute (relative) bias summary statistic
BF_sim

Example simulation from Brown and Forsythe (1974)
EDR

Compute the empirical detection rate for Type I errors and Power
aggregate_simulations

Collapse separate simulation files into a single result
Generate

Generate data
add_missing

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