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Multiple hypothesis testing is a fundamental problem in high dimensional inference, with wide applications in many scientific fields. In genome-wide association studies, tens of thousands of tests are performed simultaneously to find if any…

Methodology · Statistics 2010-12-21 Xu Han , Weijie Gu , Jianqing Fan

False discovery rate (FDR) procedures provide misleading inference when testing multiple null hypotheses with heterogeneous multinomial data. For example, in the motivating study the goal is to identify species of bacteria near the roots of…

Methodology · Statistics 2015-11-05 Joshua Habiger , David Watts , Michael Anderson

We study Bayesian inference in the spiked covariance model, where a small number of spiked eigenvalues dominate the spectrum. Our goal is to infer the spiked eigenvalues, their corresponding eigenvectors, and the number of spikes, providing…

Statistics Theory · Mathematics 2025-08-20 Kwangmin Lee , Sewon Park , Seongmin Kim , Jaeyong Lee

Bayesian statistics has gained popularity in psychological research due to its intuitive uncertainty quantification and convenient information-updating rules. In many applications, however, prior distributions are introduced merely as…

Methodology · Statistics 2026-03-10 Yang Liu , Jonathan P. Williams , Jan Hannig

This paper is a review of the popular Benjamini Hochberg Method and other related useful methods of Multiple Hypothesis testing. This is written with the purpose of serving a short but complete easy to understand review of the main article…

Methodology · Statistics 2014-06-30 Anish Acharya

In this paper, I apply the decision theory and empirical Bayesian approach to construct confidence intervals for selected populations when true parameters follow a mixture prior distribution. A loss function with two tuning parameters $k_1$…

Statistics Theory · Mathematics 2009-01-16 Zhigen Zhao

Bayesian methods provide a natural means for uncertainty quantification, that is, credible sets can be easily obtained from the posterior distribution. But is this uncertainty quantification valid in the sense that the posterior credible…

Statistics Theory · Mathematics 2020-10-02 Ryan Martin , Bo Ning

In many large scale multiple testing applications, the hypotheses often have a known graphical structure, such as gene ontology in gene expression data. Exploiting this graphical structure in multiple testing procedures can improve power as…

Methodology · Statistics 2018-12-04 Wenge Guo , Gavin Lynch , Joseph P. Romano

In recent years, multiple hypothesis testing has come to the forefront of statistical research, ostensibly in relation to applications in genomics and some other emerging fields. The false discovery rate (FDR) and its variants provide very…

Statistics Theory · Mathematics 2008-12-18 Subhashis Ghosal , Anindya Roy , Yongqiang Tang

This paper revisits the following open question in simultaneous testing of multivariate normal means against two-sided alternatives: Can the method of Benjamini and Hochberg (BH, 1995) control the false discovery rate (FDR) without imposing…

Statistics Theory · Mathematics 2023-04-12 Sanat K. Sarkar

The concept of $k$-FWER has received much attention lately as an appropriate error rate for multiple testing when one seeks to control at least $k$ false rejections, for some fixed $k\ge 1$. A less conservative notion, the $k$-FDR, has been…

Statistics Theory · Mathematics 2009-06-18 Sanat K. Sarkar , Wenge Guo

False discovery rate (FDR) controlling procedures provide important statistical guarantees for the replicability in signal identification based on multiple hypotheses testing. In many fields of study, FDR controlling procedures are used in…

Methodology · Statistics 2022-10-04 Ran Dai , Cheng Zheng

Multiple hypothesis testing with false discovery rate (FDR) control is a fundamental problem in statistical inference, with broad applications in genomics, drug screening, and outlier detection. In many such settings, researchers may have…

Methodology · Statistics 2026-02-19 Yonghoon Lee , Meshi Bashari , Edgar Dobriban , Yaniv Romano

Posterior sampling with the spike-and-slab prior [MB88], a popular multimodal distribution used to model uncertainty in variable selection, is considered the theoretical gold standard method for Bayesian sparse linear regression [CPS09,…

Machine Learning · Statistics 2025-03-05 Syamantak Kumar , Purnamrita Sarkar , Kevin Tian , Yusong Zhu

We show that the control of the false discovery rate (FDR) for a multiple testing procedure is implied by two coupled simple sufficient conditions. The first one, which we call ``self-consistency condition'', concerns the algorithm itself,…

Statistics Theory · Mathematics 2008-10-21 Gilles Blanchard , Etienne Roquain

Stability and reproducibility are essential considerations in various applications of statistical methods. False Discovery Rate (FDR) control methods are able to control false signals in scientific discoveries. However, many FDR control…

Methodology · Statistics 2025-12-22 Jiajun Sun , Zhanrui Cai , Wei Zhong

The False Discovery Rate (FDR) paradigm aims to attain certain control on Type I errors with relatively high power for multiple hypothesis testing. The Benjamini--Hochberg (BH) procedure is a well-known FDR controlling procedure. Under a…

Statistics Theory · Mathematics 2007-11-06 Zhiyi Chi

Multiple testing with false discovery rate (FDR) control has been widely conducted in the ``discrete paradigm" where p-values have discrete and heterogeneous null distributions. However, in this scenario existing FDR procedures often lose…

Methodology · Statistics 2019-07-23 Xiongzhi Chen , R. W. Doerge , Sanat K. Sarkar

We consider statistical hypothesis testing simultaneously over a fairly general, possibly uncountably infinite, set of null hypotheses, under the assumption that a suitable single test (and corresponding $p$-value) is known for each…

Methodology · Statistics 2014-02-10 Gilles Blanchard , Sylvain Delattre , Etienne Roquain

Large-scale multiple two-sample {\em Student}'s $t$ testing problems often arise from the statistical analysis of scientific data. To detect components with different values between two mean vectors, a well-known procedure is to apply the…

Methodology · Statistics 2014-10-17 Weidong Liu