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False Discovery Rate Control under Archimedean Copula
Clayton copula exchangeability Gumbel cop-ula linear step-up test multiple hypotheses testing,p-values
2013/6/14
We prove that the linear step-up procedure $\vp^{LSU}$ considered by Benjamini and Hochberg (1995) controls the false discovery rate (FDR) in the case of dependent $p$-values whose dependency structur...
Intrinsic Bounds and False Discovery Rate Control in Multiple Testing Problems
Multiple testing False Discovery Rate Benjamini Hochberg’s procedure power criticality proportion of true null hypotheses
2010/3/11
When testing a large number of independent hypotheses, three different questions are of
interest: are some hypotheses true alternatives? How many of them? Which of them?
These questions give rise to...
Sample size and positive false discovery rate control for multiple testing
Multiple hypothesis testing pFDR large deviations
2009/9/16
Positive false discovery rate (pFDR) is a useful overall measure of errors for multiple hypothesis testing, especially when the underlying goal is to attain one or more discoveries. Control of pFDR cr...
Multivariate statistics are often available as well as necessary in hypothesis tests. We study how to use such statistics to control not only false discovery rate (FDR) but also positive FDR (pFDR) wi...
Optimal weighting for false discovery rate control
False discovery rate multiple testing p-value weighting power maximization
2009/9/16
How to weigh the Benjamini-Hochberg procedure? In the context of multiple hypothesis testing, we propose a new step-wise procedure that controls the false discovery rate (FDR) and we prove it to be mo...
Feature selection in omics prediction problems using cat scores and false non-discovery rate control
Feature selection omics prediction problems cat scores false non-discovery rate control
2010/3/18
We revisit the problem of feature selection in linear discriminant analysis (LDA),
i.e. when features are correlated. First, we introduce a pooled centroids formulation
of the multi-class LDA predic...
Multivariate statistics are often available as well as necessary
in hypothesis tests. We study how to use such statistics to control not only
false discovery rate (FDR) but also positive FDR (pFDR) ...
Sample size and positive false discovery rate control for multiple testing
Multiple hypothesis testing pFDR large deviations
2010/4/27
The positive false discovery rate (pFDR) is a useful overall measure
of errors for multiple hypothesis testing, especially when the underlying
goal is to attain one or more discoveries. Control of p...