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The present paper establishes new multiple procedures for simultaneous testing of a large number of hypotheses under dependence. Special attention is devoted to experiments with rare false hypotheses. This sparsity assumption is typically…

Statistics Theory · Mathematics 2019-10-01 Marc Ditzhaus , Arnold Janssen

We argue that Bonferroni correction is a better choice for online experimentation than it is commonly given credit for. The case rests on four considerations. First, it is the simplest broadly implementable FWER-controlling method that…

Methodology · Statistics 2026-04-13 Mårten Schultzberg

This paper investigates an open issue related to false discovery rate (FDR) control of step-up-down (SUD) multiple testing procedures. It has been established in earlier literature that for this type of procedure, under some broad…

Methodology · Statistics 2011-08-29 Gilles Blanchard , Thorsten Dickhaus , Etienne Roquain , Fanny Villers

The closure principle is a standard tool for achieving strong family-wise error rate (FWER) control in multiple testing problems. We develop an e-value-based closed testing framework that inherits nice properties of e-values, which are…

Methodology · Statistics 2026-05-19 Will Hartog , Lihua Lei

Most normality tests in the literature are performed for scalar and independent samples. Thus, they become unreliable when applied to colored processes, hampering their use in realistic scenarios.We focus on Mardia's multivariate kurtosis,…

Methodology · Statistics 2022-03-02 Sara Elbouch , Olivier Michel , Pierre Comon

Heavy-tailed combination tests, such as the Cauchy combination test and harmonic mean p-value method, are widely used for testing global null hypotheses by aggregating dependent p-values. However, their theoretical guarantees under general…

Statistics Theory · Mathematics 2025-08-11 Lin Gui , Tiantian Mao , Jingshu Wang , Ruodu Wang

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

This paper investigates the (conditional) quasi-likelihood ratio test for the threshold in MA models. Under the hypothesis of no threshold, it is shown that the test statistic converges weakly to a function of the centred Gaussian process.…

Statistics Theory · Mathematics 2007-06-13 Shiqing Ling , Howell Tong

When dealing with the problem of simultaneously testing a large number of null hypotheses, a natural testing strategy is to first reduce the number of tested hypotheses by some selection (screening or filtering) process, and then to…

Methodology · Statistics 2017-03-21 Wenge Guo , Joseph P. Romano

Closed testing procedures are classically used for familywise error rate (FWER) control, but they can also be used to obtain simultaneous confidence bounds for the false discovery proportion (FDP) in all subsets of the hypotheses. In this…

Methodology · Statistics 2019-11-15 Jelle Goeman , Rosa Meijer , Thijmen Krebs , Aldo Solari

Let $(X_k)_{k\geq1}$ be a Gaussian long-range dependent process with $EX_1=0$, $EX_1^2=1$ and covariance function $r(k)=k^{-D}L(k)$. For any measurable function $G$ let $(Y_k)_{k\geq1}=(G(X_k))_{k\geq1}$. We study the asymptotic behaviour…

Probability · Mathematics 2014-10-22 Jannis Buchsteiner

The theocratical properties of the power of the conventional testing hypotheses and the selection bias are usually unknown under covariate-adaptive randomized clinical trials. In the literature, most studies are based on simulations. In…

Statistics Theory · Mathematics 2021-05-04 Li-Xin Zhang

Multiple testing is a fundamental problem in high-dimensional statistical inference. Although many methods have been proposed to control false discoveries, it is still a challenging task when the tests are correlated to each other. To…

Statistics Theory · Mathematics 2022-07-06 Meng Mei , Yuan Jiang

We consider the problem of two-sample testing in a semi-supervised setting with abundant unlabeled covariate data. Standard two-sample tests neglect covariate information, which has the potential to significantly boost performance. However,…

Machine Learning · Statistics 2026-05-05 Gyumin Lee , Shubhanshu Shekhar , Ilmun Kim

We consider inference on the first principal direction of a $p$-variate elliptical distribution. We do so in challenging double asymptotic scenarios for which this direction eventually fails to be identifiable. In order to achieve…

Statistics Theory · Mathematics 2019-08-30 Davy Paindaveine , Julien Remy , Thomas Verdebout

In this paper, we consider the problem of simultaneous testing of multivariate normal means under arbitrary covariance dependence. Specifically, let $\boldsymbol{X}\sim N_n(\boldsymbol{\theta},\boldsymbol{\Sigma})$, where…

Statistics Theory · Mathematics 2026-05-29 Prasenjit Ghosh , Arijit Chakrabarti

The family-wise error rate (FWER) has been widely used in genome-wide association studies. With the increasing availability of functional genomics data, it is possible to increase the detection power by leveraging these genomic functional…

Methodology · Statistics 2020-12-25 Huijuan Zhou , Xianyang Zhang , Jun Chen

We study the weak convergence of conditional empirical copula processes, when the conditioning event has a nonzero probability. The validity of several bootstrap schemes is stated, including the exchangeable bootstrap. We define general -…

Statistics Theory · Mathematics 2020-08-24 Alexis Derumigny , Jean-David Fermanian

In this paper, our interest is in the problem of simultaneous hypothesis testing when the test statistics corresponding to the individual hypotheses are possibly correlated. Specifically, we consider the case when the test statistics…

Statistics Theory · Mathematics 2019-01-14 Anupam Kundu , Subir Kumar Bhandari

Testing multiple hypotheses of conditional independence with provable error rate control is a fundamental problem with various applications. To infer conditional independence with family-wise error rate (FWER) control when only summary…

Methodology · Statistics 2023-10-17 Catherine Xinrui Yu , Jiaqi Gu , Zhaomeng Chen , Zihuai He