efdr_search: Bayesian EFDR optimisation.

In bayefdr: Bayesian Estimation and Optimisation of Expected False Discovery Rate

Bayesian EFDR optimisation.

Description

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

Usage

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)

bayefdr documentation built on Oct. 27, 2022, 1:05 a.m.