bh.test: Benjamini-Hochberg-Procedure

In jobstdavid/eppverification: Verification Tools for the Statistical Postprocessing of Ensemble Forecasts

Benjamini-Hochberg-Procedure

Description

This function performs the Benjamini-Hochberg-Procedure for different p-values in the multiple testing setting. This function computes the significance of the individual tests.

Usage

bh.test(p, alpha = 0.05, na.action = na.omit)

Arguments

p	vector of p-values on which the Benjamini-Hochberg-Procedure should be applied
alpha	numeric; false discovery rate at level alpha; alpha is number between 0 and 1
na.action	function to handle the NA's. Default: na.omit.

Value

A logical vector where the value TRUE indicates that the p-value at the corresponding position is significant after the Benjamini-Hochberg-Procedure with false discovery rate alpha. If the value is FALSE the p-value at the corresponding position is not significant after the Benjamini-Hochberg-Procedure with false discovery rate alpha.

Author(s)

David Jobst

References

Benjamini, Y. and Hochberg, Y. (1995). Controlling the False Discovery Rate: A Practical and Powerful Approach to Multiple Testing. Journal of the Royal Statistical Society, 57, 289-300.

Examples

# simulated data
p <- runif(100, 0, 0.06)

# Benjamini-Hochberg-Procedure
bh.test(p = p)
bh.test(p = p, alpha = 0.1)

jobstdavid/eppverification documentation built on May 13, 2024, 5:20 p.m.