adaptiveSTS | R Documentation |
Storey-Taylor-Siegmund's (2004) adaptive step-up procedure
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 |
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)
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