where 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
criticalValues
A numeric vector containing critical values used in the step-up-down test
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.