twostageBR: Blanchard-Roquain (2009) 2-stage adaptive step-up...

In mutoss: Unified Multiple Testing Procedures

Blanchard-Roquain (2009) 2-stage adaptive step-up...

Description

Blanchard-Roquain (2009) 2-stage adaptive step-up

Usage

twostageBR(pValues, alpha, lambda=1, silent=FALSE)

Arguments

pValues	the used p-values (assumed to be independent)
alpha	the level at which the FDR should be controlled.
lambda	parameter of the procedure, should belong to (0, 1/alpha) (lambda=1 default)
silent	if true any output on the console will be suppressed.

Details

This is an adaptive linear step-up procedure where the proportion of true nulls is estimated using the Blanchard-Roquain 1-stage procedure with parameter lambda, via the formula

estimated pi_0 = ( m - R(alpha,lambda) + 1) / ( m*( 1 - lambda * alpha ) )

where R(alpha,lambda) is the number of hypotheses rejected by the BR 1-stage procedure, alpha is the level at which FDR should be controlled and lambda an arbitrary parameter belonging to (0, 1/alpha) with default value 1. This procedure controls FDR at the desired level when the p-values are independent.

Value

A list containing:

rejected	A logical vector indicating which hypotheses are rejected
errorControl	A Mutoss S4 class of type errorControl, containing the type of error controlled by the function and the level alpha.

Author(s)

GillesBlanchard

References

Blanchard, G. and Roquain, E. (2009) Adaptive False Discovery Rate Control under Independence and Dependence Journal of Machine Learning Research 10:2837-2871.

mutoss documentation built on March 31, 2023, 8:46 p.m.