Blanchard-Roquain (2009) 2-stage adaptive step-up
twostageBR(pValues, alpha, lambda=1, silent=FALSE)A list containing:
A logical vector indicating which hypotheses are rejected
A Mutoss S4 class of type errorControl, containing the type of error controlled by the function and the level alpha.
GillesBlanchard
the used p-values (assumed to be independent)
the level at which the FDR should be controlled.
parameter of the procedure, should belong to (0, 1/alpha) (lambda=1 default)
if true any output on the console will be suppressed.
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.
Blanchard, G. and Roquain, E. (2009) Adaptive False Discovery Rate Control under Independence and Dependence Journal of Machine Learning Research 10:2837-2871.