A unified approach to false discovery rate estimation

@article{Strimmer2008AUA,
  title={A unified approach to false discovery rate estimation},
  author={Korbinian Strimmer},
  journal={BMC Bioinformatics},
  year={2008},
  volume={9},
  pages={303 - 303}
}
False discovery rate (FDR) methods play an important role in analyzing high-dimensional data. There are two types of FDR, tail area-based FDR and local FDR, as well as numerous statistical algorithms for estimating or controlling FDR. These differ in terms of underlying test statistics and procedures employed for statistical learning. A unifying algorithm for simultaneous estimation of both local FDR and tail area-based FDR is presented that can be applied to a diverse range of test statistics… CONTINUE READING
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