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In this paper, we approach the variance changepoints detection problem from a multiple testing setting. After proving that the standard Step-Up and Step-Down procedures are inadmissible for the standa...
A topological multiple testing approach to peak detection is proposed for the problem of detecting transcription factor binding sites in ChIP-Seq data. After kernel smoothing of the tag counts over th...
We are thankful to the three discussants for their helpful and stimulating comments to our work. We value especially the many suggestions for extensions of the methodology given by all three discussan...
Closure-based multiple testing procedures for con-trolling the familywise error rate (FWER) have been around for decades, but they have not been well un-derstood, and hence have been under-appreciated...
I want to congratulate the authors on this thought-provoking and important paper on multiple testing in exploratory settings.Standard Multiple Testing procedures can appear very mechanistic. Hypothese...
Goeman and Solari [Statist. Sci.26 (2011) 584–597] have addressed the interesting topic of multiple testing for exploratory re-search, and provided us with nice suggestions for exploratory analysis.Th...
Motivated by the practice of exploratory research, we for-mulate an approach to multiple testing that reverses the conventional roles of the user and the multiple testing procedure. Traditionally, the...
We propose a flexible and identifiable version of the two-groups model, motivated by hierarchical Bayes considerations, that features an empirical null and a semiparametric mixture model for the non-n...
Test statistics are often strongly dependent in large-scale multiple testing applications. Most corrections for multiplicity are unduly conservative for correlated test statistics, resulting in a loss...
We study statistical detection of grayscale objects in noisy images. The object of interest is of unknown shape and has an unknown intensity, that can be varying over the object and can be negative. N...
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...
We investigate the asymptotic optimality of a large class of multiple testing rules using the framework of Bayesian Decision Theory. We consider a parametric setup, in which observations come from a...
An important estimation problem that is closely related to largescale multiple testing is that of estimating the null density and the proportion of nonnull effects. A few estimators have been introd...
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...
Consider an R x C contingency table in which the categories are ordered. Multiple testing of the hypotheses that each local odds ratio is one is carried out. The methodology to perform the multiple te...

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