indepBR | R Documentation |
Blanchard-Roquain (2009) 1-stage adaptive step-up
indepBR(pValues, alpha, lambda=1, silent=FALSE)
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. |
This is a step-up procedure with critical values
C_i = alpha * min( i * ( 1 - lambda * alpha) / (m - i + 1) , lambda )
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.
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 |
GillesBlanchard
Blanchard, G. and Roquain, E. (2009) Adaptive False Discovery Rate Control under Independence and Dependence Journal of Machine Learning Research 10:2837-2871.
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