twostageBR: Blanchard-Roquain (2009) 2-stage adaptive step-up...
In mutoss: Unified multiple testing procedures

Description Usage Arguments Details Value Author(s) References

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

1	twostageBR(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 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.

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`.

GillesBlanchard

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 May 2, 2019, 5:56 p.m.