CDfdr: A Comparison Density Approach to Local False Discovery Rate Estimation
Methodology
2013-08-13 v1 Statistics Theory
Applications
Machine Learning
Statistics Theory
Abstract
Efron et al. (2001) proposed empirical Bayes formulation of the frequentist Benjamini and Hochbergs False Discovery Rate method (Benjamini and Hochberg,1995). This article attempts to unify the `two cultures' using concepts of comparison density and distribution function. We have also shown how almost all of the existing local fdr methods can be viewed as proposing various model specification for comparison density - unifies the vast literature of false discovery methods under one concept and notation.
Cite
@article{arxiv.1308.2403,
title = {CDfdr: A Comparison Density Approach to Local False Discovery Rate Estimation},
author = {Subhadeep Mukhopadhyay},
journal= {arXiv preprint arXiv:1308.2403},
year = {2013}
}