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The existence of a (p-)optimal propositional proof system is a major open question in (proof) complexity; many people conjecture that such systems do not exist. Krajicek and Pudlak (1989) show that this question is equivalent to the…

Computational Complexity · Computer Science 2010-02-03 Edward A. Hirsch , Dmitry Itsykson

This paper develops a new framework for indirect statistical inference with guaranteed necessity and sufficiency, applicable to continuous random variables. We prove that when comparing exponentially transformed order statistics from an…

Statistics Theory · Mathematics 2025-09-25 Z Zhang , X Hu , C Lu , T Liu

We consider a class of hypothesis testing problems where the null hypothesis postulates $M$ distributions for the observed data, and there is only one possible distribution under the alternative. We show that one can use a stochastic mirror…

Since the two seminal papers by Fisher (1915, 1921) were published, the test under a fixed value correlation coefficient null hypothesis for the bivariate normal distribution constitutes an important statistical problem. In the framework of…

Statistics Theory · Mathematics 2022-09-27 María Jaenada , Elena Castilla , Nirian Martín , Leandro Pardo

In this paper, we deal with sequential testing of multiple hypotheses. In the general scheme of construction of optimal tests based on the backward induction, we propose a modification which provides a simplified (generally speaking,…

Methodology · Statistics 2024-06-04 Andrey Novikov

Tze Leung Lai made seminal contributions to sequential analysis, particularly in sequential hypothesis testing, changepoint detection and nonlinear renewal theory. His work established fundamental optimality results for the sequential…

Other Statistics · Statistics 2025-10-28 Alexander G. Tartakovsky , Jay Bartroff , Cheng-Der Fuh , Haipeng Xing

E-variables are nonnegative random variables with expected value at most one under any distribution from a given null hypothesis. Every nonasymptotically valid test can be obtained by thresholding some e-variable. As such, e-variables arise…

Statistics Theory · Mathematics 2026-02-06 Martin Larsson , Aaditya Ramdas , Johannes Ruf

This paper proposes a max-test for testing (possibly infinitely) many zero parameter restrictions in an extremum estimation framework. The test statistic is formed by estimating key parameters one at a time based on many empirical loss…

Statistics Theory · Mathematics 2022-04-12 Jonathan B. Hill

We propose a simple and intuitive test for arguably the most prevailing hypothesis in statistics that data are independent and identically distributed (IID), based on a newly introduced off-diagonal sequential U-process. This IID test is…

Methodology · Statistics 2025-06-30 Tongyu Li , Jonas Mueller , Fang Yao

This paper proposes novel tests for the absence of jumps in a univariate semimartingale and for the absence of common jumps in a bivariate semimartingale. Our methods rely on ratio statistics of power variations based on irregular…

Statistics Theory · Mathematics 2017-12-21 Ole Martin , Mathias Vetter

Distribution testing can be described as follows: $q$ samples are being drawn from some unknown distribution $P$ over a known domain $[n]$. After the sampling process, a decision must be made about whether $P$ holds some property, or is far…

Distributed, Parallel, and Cluster Computing · Computer Science 2020-12-04 Uri Meir

New goodness-of-fit tests for exponentiality based on a particular property of exponential law are constructed. Test statistics are functionals of U-empirical processes. The first of these statistics is of integral type, the second one is a…

Statistics Theory · Mathematics 2016-03-08 Ya. Yu. Nikitin , K. Yu. Volkova

This paper investigates a statistical procedure for testing the equality of two independent estimated covariance matrices when the number of potentially dependent data vectors is large and proportional to the size of the vectors, that is,…

Statistics Theory · Mathematics 2020-06-01 Rémy Mariétan , Stephan Morgenthaler

Models for analyzing multivariate data sets with missing values require strong, often unassessable, assumptions. The most common of these is that the mechanism that created the missing data is ignorable - a twofold assumption dependent on…

Applications · Statistics 2020-02-17 Iavor Bojinov , Natesh Pillai , Donald Rubin

We want to select the best systems out of a given set of systems (or rank them) with respect to their expected performance. The systems allow random observations only and we assume that the joint observation of the systems has a…

Methodology · Statistics 2017-01-23 Björn Görder , Michael Kolonko

Statistical models of unobserved heterogeneity are typically formalized as mixtures of simple parametric models and interest naturally focuses on testing for homogeneity versus general mixture alternatives. Many tests of this type can be…

Methodology · Statistics 2016-03-22 Jiaying Gu , Roger Koenker , Stanislav Volgushev

Exact null distributions of goodness-of-fit test statistics are generally challenging to obtain in tractable forms. Practitioners are therefore usually obliged to rely on asymptotic null distributions or Monte Carlo methods, either in the…

Methodology · Statistics 2023-09-06 Alberto Fernández-de-Marcos , Eduardo García-Portugués

We consider goodness-of-fit tests with i.i.d. samples generated from a categorical distribution $(p_1,...,p_k)$. For a given $(q_1,...,q_k)$, we test the null hypothesis whether $p_j=q_{\pi(j)}$ for some label permutation $\pi$. The…

Statistics Theory · Mathematics 2018-07-30 Chao Gao

We study a novel class of affine invariant and consistent tests for multivariate normality. The tests are based on a characterization of the standard $d$-variate normal distribution by means of the unique solution of an initial value…

Statistics Theory · Mathematics 2020-07-07 Bruno Ebner , Norbert Henze , David Strieder

The conditional randomization test (CRT) was recently proposed to test whether two random variables X and Y are conditionally independent given random variables Z. The CRT assumes that the conditional distribution of X given Z is known…

Machine Learning · Computer Science 2023-04-11 Shuai Li , Ziqi Chen , Hongtu Zhu , Christina Dan Wang , Wang Wen
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