fdrfun: Compute p-values when controlling the False Discovery Rate

In jonasbhend/geoutils: package to read in and analyse climate model output in NetCDF format

Description

Function to compute adjusted critical p-values and the fraction of test for which the alternative hypothesis might be true according to Ventura et al. (2004).

Usage

fdrfun(p, q = 0.05, log = TRUE, tight = TRUE)

Arguments

p	p-values of multiple tests
q	probability for which FDR should be controlled
log	logical, are p-values log-transformed?
tight	logical, should tighter FDR control be used

References

Ventura, V., C.J. Paciorek, and J.S. Risbey (2004). Controlling the proportion of falsely rejected hypotheses when conducting multiple tests with climatological data. Journal of Climate, 17 (22).

jonasbhend/geoutils documentation built on May 19, 2019, 7:27 p.m.