mutoss (version 0.1-7)

twostageBR: 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.

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.

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.

References

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