762
(Revised 1/03)
Christopher Genovese and Larry Wasserman
This paper extends the theory of false discovery rates (FDR) pioneered
by Benjamini and Hochberg (1995). We give statistical models
underlying multiple testing in the independent, continuous case. We
define the realized FDR and False Nondiscovery Rate (FNR) as
stochastic processes and characterize their asymptotic behavior. We
develop methods for estimating the p-value distribution, even in the
non-identifiable case. We study a class of methods that asymptotically
attains the optimal behavior. We also develop a new method for
controlling the probability of large realized FDR.
Keywords: Multiple Testing, p-values, False Discovery Rate, Bootstrap