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The group testing problem concerns discovering a small number of defective items within a large population by performing tests on pools of items. A test is positive if the pool contains at least one defective, and negative if it contains no…

Information Theory · Computer Science 2026-05-15 Matthew Aldridge , Oliver Johnson , Jonathan Scarlett

In this article, we consider the problem of simultaneous testing of hypotheses when the individual test statistics are not necessarily independent. Specifically, we consider the problem of simultaneous testing of point null hypotheses…

Statistics Theory · Mathematics 2018-07-17 Prasenjit Ghosh , Arijit Chakrabarti

A popular setting in medical statistics is a group sequential trial with independent and identically distributed normal outcomes, in which interim analyses of the sum of the outcomes are performed. Based on a prescribed stopping rule, one…

Statistics Theory · Mathematics 2018-04-03 Ben Berckmoes , Anna Ivanova , Geert Molenberghs

This paper is devoted to testing time series that exhibit behavior related to two or more regimes with different statistical properties. Motivation of our study are two real data sets from plasma physics with observable two-regimes…

Mathematical Physics · Physics 2015-06-04 Janusz gajda , Grzegorz Sikora , Agnieszka Wyłomańska

We consider a model of selective prediction, where the prediction algorithm is given a data sequence in an online fashion and asked to predict a pre-specified statistic of the upcoming data points. The algorithm is allowed to choose when to…

Machine Learning · Computer Science 2019-05-30 Mingda Qiao , Gregory Valiant

The practice of pooling several individual test statistics to form aggregate tests is common in many statistical application where individual tests may be underpowered. While selection by aggregate tests can serve to increase power, the…

Methodology · Statistics 2020-12-08 Ruth Heller , Amit Meir , Nilanjan Chatterjee

We formulate nonparametric and semiparametric hypothesis testing of multivariate stationary linear time series in a unified fashion and propose new test statistics based on estimators of the spectral density matrix. The limiting…

Statistics Theory · Mathematics 2009-09-03 Yoshihiro Yajima , Yasumasa Matsuda

This paper introduces a statistical test inferring whether a variable allows separating two classes by means of a single critical value. Its test statistic is the prediction error of a nonparametric threshold classifier. While this approach…

Methodology · Statistics 2017-07-17 Fabian Schroeder

Empirical likelihood serves as a powerful tool for constructing confidence intervals in nonparametric regression and regression discontinuity designs (RDD). The original empirical likelihood framework can be naturally extended to these…

Statistics Theory · Mathematics 2025-04-03 Qin Fang , Shaojun Guo , Yang Hong , Xinghao Qiao

A scientific reasoning system makes decisions using objective evidence in the form of independent experimental trials, propositional axioms, and constraints on the probabilities of events. As a first step towards this goal, we propose a…

Artificial Intelligence · Computer Science 2013-04-05 David Sher

Group testing is the process of pooling arbitrary subsets from a set of $n$ items so as to identify, with a minimal number of tests, a "small" subset of $d$ defective items. In "classical" non-adaptive group testing, it is known that when…

Information Theory · Computer Science 2018-09-21 Venkata Gandikota , Elena Grigorescu , Sidharth Jaggi , Samson Zhou

We establish a general concentration result for the 1-Wasserstein distance between the empirical measure of a sequence of random variables and its expectation. Unlike standard results that rely on independence (e.g., Sanov's theorem) or…

Statistics Theory · Mathematics 2026-01-13 Arash A. Amini , Luciano Vinas

Inference is the process of using facts we know to learn about facts we do not know. A theory of inference gives assumptions necessary to get from the former to the latter, along with a definition for and summary of the resulting…

Machine Learning · Statistics 2021-09-27 Beau Coker , Cynthia Rudin , Gary King

How should researchers analyze randomized experiments in which the main outcome is latent and measured in multiple ways but each measure contains some degree of error? We first identify a critical study-specific noncomparability problem in…

Econometrics · Economics 2026-01-13 Jiawei Fu , Donald P. Green

Hypothesis tests are a crucial statistical tool for data mining and are the workhorse of scientific research in many fields. Here we study differentially private tests of independence between a categorical and a continuous variable. We take…

Methodology · Statistics 2019-03-25 Simon Couch , Zeki Kazan , Kaiyan Shi , Andrew Bray , Adam Groce

When a planner must decide whether it has enough evidence to make a decision based on probability, it faces the sample size problem. Current planners using probabilities need not deal with this problem because they do not generate their…

Artificial Intelligence · Computer Science 2013-03-26 Nathaniel G. Martin , James F. Allen

A new method based on the rejection sampling for finding statistical tests is proposed. This method is conceptually intuitive, easy to implement, and applicable for arbitrary dimension. To illustrate its potential applicability, three…

Methodology · Statistics 2026-03-11 Markku Kuismin

The use of Bell's theorem in any application or experiment relies on the assumption of free choice or, more precisely, measurement independence, meaning that the measurements can be chosen freely. Here, we prove that even in the simplest…

Quantum Physics · Physics 2016-11-25 Gilles Pütz , Denis Rosset , Tomer Jack Barnea , Yeong-Cherng Liang , Nicolas Gisin

In the group testing problem the aim is to identify a small set of $k\sim n^\theta$ infected individuals out of a population size $n$, $0<\theta<1$. We avail ourselves of a test procedure capable of testing groups of individuals, with the…

Discrete Mathematics · Computer Science 2021-05-14 Amin Coja-Oghlan , Oliver Gebhard , Max Hahn-Klimroth , Philipp Loick

We study the group testing problem where the goal is to identify a set of k infected individuals carrying a rare disease within a population of size n, based on the outcomes of pooled tests which return positive whenever there is at least…

Machine Learning · Statistics 2022-06-16 Amin Coja-Oghlan , Oliver Gebhard , Max Hahn-Klimroth , Alexander S. Wein , Ilias Zadik