pSeqStop: P-Value Sequential Adjustment

In eva: Extreme Value Analysis with Goodness-of-Fit Testing

P-Value Sequential Adjustment

Description

Given a set of (ordered) p-values, returns p-values adjusted according to the ForwardStop and StrongStop stopping rules.

Usage

pSeqStop(p)

Arguments

p	Vector of p-values in the order the hypotheses are tested.

Details

Roughly speaking, under the assumption of independent but ordered p-values, the StrongStop adjusted p-values control for the familywise error rate, while ForwardStop provides control for the false discovery rate. The input order is preserved in the returned data frame.

Value

StrongStop	Vector of ordered p-values adjusted for the familywise error rate.
ForwardStop	Vector of ordered p-values adjusted for the false discovery rate.
UnAdjusted	Vector of non-transformed p-values.

References

G'Sell, M. G., Wager, S., Chouldechova, A., & Tibshirani, R. (2013). Sequential Selection Procedures and False Discovery Rate Control. arXiv preprint arXiv:1309.5352.

Benjamini, Y., & Hochberg, Y. (1995). Controlling the false discovery rate: a practical and powerful approach to multiple testing. Journal of the Royal Statistical Society. Series B (Methodological), 289-300.

Bader B., Yan J., & Zhang X. (2015). Automated Selection of r for the r Largest Order Statistics Approach with Adjustment for Sequential Testing. Department of Statistics, University of Connecticut.

Examples

x <- rgevr(500, 10, loc = 0.5, scale = 1, shape = 0.5)
y <- gevrSeqTests(x, method = "ed")
pSeqStop(y$p.values)

eva documentation built on June 21, 2026, 9:07 a.m.