HighProbability-package {HighProbability} | R Documentation |
HighProbability provides a simple, fast, reliable solution to the multiple testing problem. Given a vector of p-values or achieved significance levels computed using standard frequentist inference, HighProbability determines which ones are low enough that their alternative hypotheses can be considered highly probable. The p-value vector may be determined using existing R functions such as t.test, wilcox.test, cor.test, or sample. HighProbability can be used to detect differential gene expression and to solve other problems involving a large number of hypothesis tests.
Important functions:
alternative.probable
determines which alternative hypotheses have sufficiently high probability of truth for acceptance.
alternative.beneficial
determines which alternative hypotheses should be accepted according to a decision-theoretic approach.
David R. Bickel (DavidBickel.66846716@bloglines.com, http://www.davidbickel.com) , Zahra Montazeri (zahra@math.carleton.ca)