| hc.score {fdrtool} | R Documentation |
Compute Empirical Higher Criticism Scores and Corresponding Decision Threshold From p-Values
Description
hc.score computes the empirical higher criticism (HC) scores from p-values.
hc.thresh determines the HC decision threshold by searching for the p-value with the maximum HC score.
Usage
hc.score(pval)
hc.thresh(pval, alpha0=1, plot=TRUE)
Arguments
pval |
vector of p-values. |
alpha0 |
look only at a fraction |
plot |
show plot with HC decision threshold. |
Details
Higher Criticism (HC) provides an alternative means to determine decision thresholds for signal identification, especially if the signal is rare and weak.
See Donoho and Jin (2008) for details of this approach and Klaus and Strimmer (2012) for a review and connections with FDR methdology.
Value
hc.score returns a vector with the HC score corresponding to each p-value.
hc.thresh returns the p-value corresponding to the maximum HC score.
Author(s)
Bernd Klaus and Korbinian Strimmer (https://strimmerlab.github.io).
References
Donoho, D. and J. Jin. (2008). Higher criticism thresholding: optimal feature selection when useful features are rare and weak. Proc. Natl. Acad. Sci. USA 105:14790-15795.
Klaus, B., and K. Strimmer (2013). Signal identification for rare and weak features: higher criticism or false discovery rates? Biostatistics 14: 129-143. <DOI:10.1093/biostatistics/kxs030>
See Also
Examples
# load "fdrtool" library
library("fdrtool")
# some p-values
data(pvalues)
# compute HC scores
hc.score(pvalues)
# determine HC threshold
hc.thresh(pvalues)