context("simulation_check")
# Exemplary simulation with low number of Monte Carlo replicates
#----------------- General benchmark settings -------------------------------#
alphas <- 0.1
nreps <- 2 # number of times each simulation should be repeated (monte carlo replicates)
#------------- Simulation function ------------------------------------------#
ms <- 20000
eff_sizes <- seq(1, 2.5, length=2)
sim_funs <- lapply(eff_sizes, function(x) du_ttest_sim_fun(ms, 0.95, x, uninformative_filter = FALSE))
#------------- Methods to be benchmarked ------------------------------------#
continuous_methods_list <- list(bh,
lsl_gbh,
tst_gbh,
stratified_bh,
clfdr,
ddhf,
ihw_5fold,
ihw_bonf_5fold_reg,
bonf,
storey_qvalue)
fdr_methods <- lapply(continuous_methods_list, continuous_wrap)
#-----------------------------------------------------------------------------
eval_table <- run_evals(sim_funs, fdr_methods, nreps, alphas, BiocParallel = FALSE)
eval_table <- dplyr::mutate(eval_table,
eff_size = sapply(strsplit(sim_pars, "effect size:"), function(x) as.numeric(x[2])))
testthat::expect_equal(eval_table$nsuccessful, rep(nreps, nrow(eval_table)))
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