  False discovery rates (FDR) are typically estimated from a mixture of a null
and an alternative distribution. Here, we study a complementary approach
proposed by Rice and Spiegelhalter (2008) that uses as primary quantities the
null model and a parametric family for the local false discovery rate.
Specifically, we consider the half-normal decay and the beta-uniform mixture
models as FDR threshold functions. Using simulations and analysis of real data
we compare the performance of the Rice-Spiegelhalter approach with that of
competing FDR estimation procedures. If the alternative model is misspecified
and an empirical null distribution is employed the accuracy of FDR estimation
degrades substantially. Hence, while being a very elegant formalism, the FDR
threshold approach requires special care in actual application.
