Monte Carlo Statistical Simulation Tools Using a Functional Approach


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Documentation for package ‘mcstatsim’ version 0.9.2

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calc_bias Calculate Bias and Bias Monte Carlo Standard Error
calc_coverage Calculate Coverage Probability and its Monte Carlo Standard Error
calc_mse Calculate Mean Squared Error and its Monte Carlo Standard Error
calc_rejection_rate Calculate Rejection Rate and its Monte Carlo Standard Error
calc_relative_bias Calculate Relative Bias and its Monte Carlo Standard Error
calc_relative_mse Calculate Relative Mean Squared Error and its Monte Carlo Standard Error
calc_relative_rmse Calculate Relative Root Mean Squared Error and its Monte Carlo Standard Error
calc_rmse Calculate Root Mean Squared Error and its Monte Carlo Standard Error
calc_variance Calculate Variance and its Monte Carlo Standard Error
calc_width Calculate Average Width of Confidence Intervals and its Monte Carlo Standard Error
check_estimates Flag Non-Finite or Degenerate Estimates in Simulation Output
combine_df Combine Dataframes in a Nested List
failure_summary Summarise Failed Jobs from a Simulation Run
mcpmap Parallel Map Function using functionals::fmapn
mcse_target Replications Needed to Reach a Target Monte Carlo Standard Error
plot_convergence Convergence Trace of a Monte Carlo Estimate
plot_performance Point-Range Plot of a Performance Measure Across Conditions
plot_zip Zip Plot of Confidence-Interval Coverage
runsim Run Monte Carlo Simulations in Parallel
summarise_sim Summarise Replicate-Level Simulation Output into a Performance Table