Bayesian EFDR optimisation. — efdr

Given a vector of probabilities, this function finds the probability threshold that matches a target expected false discovery rate as closely as possible.

efdr_search(
  probs,
  target_efdr,
  min_threshold = 0.7,
  prob_thresholds = seq(0.5, 0.9995, by = 0.00025)
)

Arguments

probs: Vector of probabilities.
target_efdr: Numeric scalar specifying the expected false discovery rate to match.
min_threshold: Minimum probability threshold. If the optimal probability threshold is below this number, it is rejected and min_threshold is used instead.
prob_thresholds: Vector for probability thresholds to scan, with the aim of finding the threshold that matches the target EFDR.

Value

An object of class "bayefdr" containing the probability thresholds tested, the EFDR and EFNR at each probability threshold, and the optimal threshold.

Examples

 probs <- runif(100)
 efdr <- efdr_search(probs, target_efdr = 0.1)
 plot(efdr)