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When comparing two distributions, it is often helpful to learn at which quantiles or values there is a statistically significant difference. This provides more information than the binary "reject" or "do not reject" decision of a global…

Statistics Theory · Mathematics 2018-08-16 Matt Goldman , David M. Kaplan

We consider the problem of testing the equality of conditional distributions of a response variable given a vector of covariates between two populations. Such a hypothesis testing problem can be motivated from various machine learning and…

Methodology · Statistics 2023-02-24 Xiaoyu Hu , Jing Lei

In this paper, two tests, based on CUSUM of the residuals and least squares estimation, are studied to detect in real time a change-point in a nonlinear model. A first test statistic is proposed by extension of a method already used in the…

Statistics Theory · Mathematics 2013-02-28 Gabriela Ciuperca

We address the issue of lack-of-fit testing for a parametric quantile regression. We propose a simple test that involves one-dimensional kernel smoothing, so that the rate at which it detects local alternatives is independent of the number…

Statistics Theory · Mathematics 2014-06-13 Samuel Maistre , Pascal Lavergne , Valentin Patilea

We investigate properties of a bootstrap-based methodology for testing hypotheses about equality of certain characteristics of the distributions between different populations in the context of functional data. The suggested testing…

Statistics Theory · Mathematics 2016-09-29 Efstathios Paparoditis , Theofanis Sapatinas

The recent success of generative adversarial networks and variational learning suggests training a classifier network may work well in addressing the classical two-sample problem. Network-based tests have the computational advantage that…

Machine Learning · Statistics 2022-06-01 Xiuyuan Cheng , Alexander Cloninger

Considering two independent Poisson processes, we address the question of testing equality of their respective intensities. We first propose single tests whose test statistics are U-statistics based on general kernel functions. The…

Statistics Theory · Mathematics 2012-11-15 Magalie Fromont , Béatrice Laurent , Patricia Reynaud-Bouret

Given two networks of differing sizes, it is of interest to test whether the two networks belong to the same distribution. We formalize the notion of "equality of distribution" under the framework of the generalized random dot product…

Statistics Theory · Mathematics 2026-03-10 Joshua Agterberg , Minh Tang , Carey Priebe

This paper deals with testing the equality of $k$ ($k\ge 2$) distribution functions against possible stochastic ordering among them. Two classes of rank tests are proposed for this testing problem. The statistics of the tests under study…

Statistics Theory · Mathematics 2025-06-03 Nikolay I. Nikolov , Eugenia Stoimenova

In this work, we study non-parametric hypothesis testing problem with distribution function constraints. The empirical likelihood ratio test has been widely used in testing problems with moment (in)equality constraints. However, some…

Statistics Theory · Mathematics 2016-05-03 Yingxi Liu , Ahmed Tewfik

This paper provides a nonparametric test for the identity of two multivariate continuous distribution functions (d.f.'s) when they differ in locations. The test uses Wilcoxon rank-sum statistics on distances between observations for each of…

Applications · Statistics 2019-08-08 Soumita Modak , Uttam Bandyopadhyay

Empirical cumulative distribution functions (ECDFs) have been used to test the hypothesis that two samples come from the same distribution since the seminal contribution by Kolmogorov and Smirnov. This paper describes a statistic which is…

Methodology · Statistics 2020-07-06 Connor Dowd

Testing the equality of the covariance matrices of two high-dimensional samples is a fundamental inference problem in statistics. Several tests have been proposed but they are either too liberal or too conservative when the required…

Statistics Theory · Mathematics 2023-01-04 Jin-Ting Zhang , Jingyi Wang , Tianming Zhu

We propose a two-sample test for high-dimensional means that requires neither distributional nor correlational assumptions, besides some weak conditions on the moments and tail properties of the elements in the random vectors. This…

Methodology · Statistics 2019-04-17 Kaijie Xue , Fang Yao

We present a novel family of nonparametric omnibus tests of the hypothesis that two unknown but estimable functions are equal in distribution when applied to the observed data structure. We developed these tests, which represent a…

Statistics Theory · Mathematics 2017-06-15 Alexander R. Luedtke , Marco Carone , Mark J. van der Laan

In this paper, we construct a consistent non-parametric test for testing the equality of population medians for different samples when the observations in each sample are independent and identically distributed. This test can be further…

Methodology · Statistics 2025-01-10 Swapnaneel Bhattacharyya

We present the results of a large number of simulation studies regarding the power of various goodness-of-fit as well as nonparametric two-sample tests for univariate data. This includes both continuous and discrete data. In general no…

Methodology · Statistics 2024-11-13 Wolfgang Rolke

The comparison of a parameter in $k$ populations is a classical problem in statistics. Testing for the equality of means or variances are typical examples. Most procedures designed to deal with this problem assume that $k$ is fixed and that…

A smooth test to simultaneously compare $K$ copulas, where $K \geq 2$ is proposed. The $K$ observed populations can be paired, and the test statistic is constructed based on the differences between moment sequences, called copula…

Statistics Theory · Mathematics 2023-12-07 Yves Ismaël Ngounou Bakam , Denys Pommeret

The problem of binary hypothesis testing between two probability measures is considered. New sharp bounds are derived for the best achievable error probability of such tests based on independent and identically distributed observations.…

Information Theory · Computer Science 2024-05-30 Valentinian Lungu , Ioannis Kontoyiannis