run_evals: run_evals: Main function to benchmark FDR methods on given...

In nignatiadis/IHWpaper: Reproduce figures in IHW paper

Description

run_evals: Main function to benchmark FDR methods on given simulations.

Usage

run_evals(sim_funs, fdr_methods, nreps, alphas, ...)

Arguments

sim_funs	List of simulation settings
fdr_methods	List of FDR controlling methods to be benchmarked
nreps	Integer, number of Monte Carlo replicates for the simulations
alphas	Numeric, vector of nominal significance levels at which to apply FDR controlling methods
...	Additional arguments passed to sim_fun_eval

Details

This is the main workhorse function which runs all simulation benchmarks for IHWpaper. It receives input as described above, and the output is a data.frame with the following columns:

• fdr_method: Multiple testing method which was used

• fdr_pars: Custom parameters of the multiple testing method

• alpha: Nominal significance level at which the benchmark was run

• FDR: False Discovery Rate of benchmarked method on simulated dataset

• power: Power of benchmarked method on simulated dataset

• rj_ratio: Average rejections divided by total number of hypotheses

• FPR: False positive rate of benchmarked method on simulated dataset

• FWER: Familywise Error Rate of benchmarked method on simulated dataset

• nsuccessful: Number of successful evaluations of the method

• sim_method: Simulation scenario under which benchmark was run

• m: Total number of hypotheses

• sim_pars: Custom parameters of the simulation scenario

Value

data.frame which summarizes results of numerical experiment

Examples

   nreps <- 3 # monte carlo replicates
   ms <- 5000 # number of hypothesis tests
   eff_sizes <- c(2,3)
   sim_funs <- lapply(eff_sizes,
			function(x) du_ttest_sim_fun(ms,0.95,x, uninformative_filter=FALSE))
	  continuous_methods_list <- list(bh,
                              	  lsl_gbh,
 	                          	  clfdr,
                                   ddhf)
  fdr_methods <- lapply(continuous_methods_list, continuous_wrap)
 eval_table <- run_evals(sim_funs, fdr_methods, nreps, 0.1, BiocParallel=FALSE)

nignatiadis/IHWpaper documentation built on Jan. 18, 2021, 2:24 p.m.