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Self-testing allows classical referees to verify the quantum behaviour of some untrusted devices. Recently we developed a framework for building large self-tests by repeating a smaller self-test many times in parallel. However, the…

Quantum Physics · Physics 2017-02-13 Matthew McKague

The main results imply that the probability P(\ZZ\in A+\th) is Schur-concave/Schur-convex in (\th_1^2,\dots,\th_k^2) provided that the indicator function of a set A in \R^k is so, respectively; here, \th=(\th_1,\dots,\th_k) in \R^k and \ZZ…

Probability · Mathematics 2017-01-17 Iosif Pinelis

The main purpose of the paper is to investigate the possibility of applying Chen-Stein approach to estimate the $\chi^2$ distance between Poisson distribution and a sum of independent indicators. Earlier results concerning $\chi^2$ distance…

Probability · Mathematics 2021-09-13 Vytas Zacharovas

Exact expressions are given for the distribution function of the ratio of a weighted sum of independent chi-squared variables to a single chi-square variable, scaled appropriately. This distribution is the generalization of the classical F…

Classical Analysis and ODEs · Mathematics 2011-03-30 Charles F. Dunkl , Donald E. Ramirez

Two-sample tests for multivariate data and non-Euclidean data are widely used in many fields. Parametric tests are mostly restrained to certain types of data that meets the assumptions of the parametric models. In this paper, we study a…

Methodology · Statistics 2018-05-01 Hao Chen , Xu Chen , Yi Su

We report on a series of experiments concerning the feasibility of example driven modelling. The main aim was to establish experimentally within an academic environment: the relationship between error and task complexity using a)…

Human-Computer Interaction · Computer Science 2008-03-10 Simon R. Thorne , David Ball , Z. Lawson

We consider a robust version of the classical Wald test statistics for testing simple and composite null hypotheses for general parametric models. These test statistics are based on the minimum density power divergence estimators instead of…

Statistics Theory · Mathematics 2016-07-04 Abhik Ghosh , Abhijit Mandal , Nirian Martin , Leandro Pardo

There are many applications that benefit from computing the exact divergence between 2 discrete probability measures, including machine learning. Unfortunately, in the absence of any assumptions on the structure or independencies within…

Machine Learning · Computer Science 2023-10-16 Loong Kuan Lee , Nico Piatkowski , François Petitjean , Geoffrey I. Webb

Two-sample tests evaluate whether two samples are realizations of the same distribution (the null hypothesis) or two different distributions (the alternative hypothesis). We consider a new setting for this problem where sample features are…

Machine Learning · Computer Science 2022-07-20 Weizhi Li , Gautam Dasarathy , Karthikeyan Natesan Ramamurthy , Visar Berisha

The class of dual $\phi$-divergence estimators (introduced in Broniatowski and Keziou (2009) is explored with respect to robustness through the influence function approach. For scale and location models, this class is investigated in terms…

Statistics Theory · Mathematics 2009-12-15 Aida Toma , Michel Broniatowski

We examine the $\chi^2$ test for binned, Gaussian samples, including effects due to the fact that the experimentally available sample standard deviation and the unavailable true standard deviation have different statistical properties. For…

Data Analysis, Statistics and Probability · Physics 2019-08-27 Nicholas R. Hutzler

We propose and analyze algorithms for distributionally robust optimization of convex losses with conditional value at risk (CVaR) and $\chi^2$ divergence uncertainty sets. We prove that our algorithms require a number of gradient…

Optimization and Control · Mathematics 2020-12-14 Daniel Levy , Yair Carmon , John C. Duchi , Aaron Sidford

We describe a general framework for weighted parametric multiple test procedures based on the closure principle. We utilize general weighting strategies that can reflect complex study objectives and include many procedures in the literature…

Methodology · Statistics 2019-08-14 Dong Xi , Ekkehard Glimm , Willi Maurer , Frank Bretz

Two-sample inference for the difference of population means typically relies upon a Central Limit Theorem approximation. When data are drawn from a Negative Binomial distribution, previous work of Shilane et al. (2010) showed that a Normal…

Methodology · Statistics 2012-03-06 David Shilane , Derek Bean

The study of mixture models constitutes a large domain of research in statistics. In the first part of this work, we present phi-divergences and the existing methods which produce robust estimators. We are more particularly interested in…

Methodology · Statistics 2016-11-28 Diaa Al Mohamad

Recently Liu and Wang derived the likelihood ratio test (LRT) statistic and its asymptotic distribution for testing equality of two multinomial distributions vs. the alternative that the second distribution is larger in terms of increasing…

Statistics Theory · Mathematics 2007-06-13 Arthur Cohen , John Kolassa , Harold Sackrowitz

We introduce credal two-sample testing, a new hypothesis testing framework for comparing credal sets -- convex sets of probability measures where each element captures aleatoric uncertainty and the set itself represents epistemic…

Machine Learning · Statistics 2025-03-14 Siu Lun Chau , Antonin Schrab , Arthur Gretton , Dino Sejdinovic , Krikamol Muandet

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 likelihood ratio test is widely used in exploratory factor analysis to assess the model fit and determine the number of latent factors. Despite its popularity and clear statistical rationale, researchers have found that when the…

Statistics Theory · Mathematics 2025-01-08 Yinqiu He , Zi Wang , Gongjun Xu

We provide new limit theory for functionals of a general class of processes lying at the boundary between stationarity and nonstationarity -- what we term weakly nonstationary processes (WNPs). This includes, as leading examples, fractional…

Statistics Theory · Mathematics 2020-08-17 James A. Duffy , Ioannis Kasparis