adaptiveSTS: Storey-Taylor-Siegmund (2004) adaptive step-up procedure
In mutoss: Unified multiple testing procedures

Description Usage Arguments Details Value Author(s) References Examples

Storey-Taylor-Siegmund's (2004) adaptive step-up procedure

1	adaptiveSTS(pValues, alpha, lambda=0.5, silent=FALSE)

`pValues`	The used raw pValues.
`alpha`	The level at which the FDR shall be controlled.
`lambda`	The tuning parameter for the estimation procedure (defaults to 0.5)
`silent`	If true any output on the console will be suppressed.

The adaptive STS procedure uses a conservative estimate of pi0 which is plugged in a linear step-up procedure. The estimation of pi0 requires a parameter (lambda) which is set to 0.5 by default. Note that the estimated pi0 is truncated at 1 as suggested by the author, so the implemetation of the procedure is not entirely supported by the proof in the reference.

A list containing:

`adjPValues`	A numeric vector containing the adjusted pValues
`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`.

Werft Wiebke

Storey, J.D., Taylor, J.E. and Siegmund, D. (2004). Strong control, conservative point estimation and simultaneous conservative consistency of false discovery rates: a unified approach. Journal of the Royal Statistical Society, B 66(1):187-205.

alpha <- 0.05
p <-c(runif(10, min=0, max=0.01), runif(10, min=0.9,max=1))
result <- adaptiveSTS(p, alpha, lambda=0.5)
result <- adaptiveSTS(p, alpha, lambda=0.5, silent=TRUE)