mutoss (version 0.1-4)

adaptiveSTS: Storey-Taylor-Siegmund (2004) adaptive step-up procedure

Description

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

Usage

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

Arguments

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.

Value

• 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.

Details

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.

References

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.

Examples

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)