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A fundamental functional in nonparametric statistics is the Mann-Whitney functional ${\theta} = P (X < Y )$ , which constitutes the basis for the most popular nonparametric procedures. The functional ${\theta}$ measures a location or…

Methodology · Statistics 2023-11-30 Jonas Beck , Patrick B. Langthaler , Arne C. Bathke

The growing availability of large health databases has expanded the use of observational studies for comparative effectiveness research. Unlike randomized trials, observational studies must adjust for systematic differences in patient…

Methodology · Statistics 2026-01-21 Haidong Lu , Fan Li , Laine E. Thomas , Fan Li

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

Consider two random variables contaminated by two unknown transformations. The aim of this paper is to test the equality of those transformations. Two cases are distinguished: first, the two random variables have known distributions.…

Methodology · Statistics 2011-11-01 Mohamed Boutahar , Denys Pommeret

Testing equality of two multivariate distributions is a classical problem for which many non-parametric tests have been proposed over the years. Most of the popular two-sample tests, which are asymptotically distribution-free, are based…

Statistics Theory · Mathematics 2019-04-17 Bhaswar B. Bhattacharya

We propose a two-sample test for large-dimensional covariance matrices in generalized elliptical models. The test statistic is based on a U-statistic estimator of the squared Frobenius norm of the difference between the two population…

Statistics Theory · Mathematics 2025-07-04 Nina Dörnemann

In this paper, we propose a novel approach to test the equality of high-dimensional mean vectors of several populations via the weighted $L_2$-norm. We establish the asymptotic normality of the test statistics under the null hypothesis. We…

Statistics Theory · Mathematics 2024-02-01 Jianghao Li , Zhenzhen Niu , Shizhe Hong , Zhidong Bai

Most existing methods for testing equality of means of functional data from multiple populations rely on assumptions of equal covariance and/or Gaussianity. In this work we provide a new testing method based on a statistic that is…

Methodology · Statistics 2025-09-30 Chuang Xu , Andrew T. A. Wood , Yanrong Yang

Testing the homogeneity of two distributions is fundamental in statistics, but classical procedures may fail under nonignorable nonresponse. In many surveys, callback data record repeated contact attempts and provide auxiliary information…

Methodology · Statistics 2026-04-24 Xinyu Wang , Tao Yu , Chunlin Wang , Pengfei Li

Assume that we have a random sample from an absolutely continuous distribution (univariate, or multivariate) with a known functional form and some unknown parameters. In this paper, we have studied several parametric tests based on…

Statistics Theory · Mathematics 2024-05-14 Rahul Singh , Neeraj Misra

Graph-based tests are a class of non-parametric two-sample tests useful for analyzing high-dimensional data. The test statistics are constructed from similarity graphs (such as K-minimum spanning tree), and consequently, their performance…

Methodology · Statistics 2025-06-23 Yichuan Bai , Lynna Chu

Inverse normal transformations applied to the partially overlapping samples t-tests by Derrick et.al. (2017) are considered for their Type I error robustness and power. The inverse normal transformation solutions proposed in this paper are…

Computation · Statistics 2017-08-02 Ben Derrick , Paul White , Deirdre Toher

Overlapping coefficient is a direct measure of similarity between two distributions which is recently becoming very useful. This paper investigates estimation for some well-known measures of overlap, namely Matusita's measure $\rho$,…

Methodology · Statistics 2019-10-08 Hamza Dhaker , El Hadji Deme , Salah El-Adlouni

The two-sample problem, which consists in testing whether independent samples on $\mathbb{R}^d$ are drawn from the same (unknown) distribution, finds applications in many areas. Its study in high-dimension is the subject of much attention,…

Statistics Theory · Mathematics 2023-02-09 Stephan Clémençon , Myrto Limnios , Nicolas Vayatis

Kernel two-sample tests have been widely used for multivariate data to test equality of distributions. However, existing tests based on mapping distributions into a reproducing kernel Hilbert space mainly target specific alternatives and do…

Methodology · Statistics 2023-11-21 Hoseung Song , Hao Chen

It is known that Bernoulli scheme of independent trials with two outcomes is connected with the binomial coefficients. The aim of this paper is to indicate stochastic processes which are connected with the $q$-polynomial coefficients (in…

Combinatorics · Mathematics 2007-05-23 Alexander I. Il'inskii

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…

This article is devoted to the study of overlap measures of densities of two exponential populations. Various Overlapping Coefficients, namely: Matusita's measure $\rho$, Morisita's measure $\lambda$ and Weitzman's measure $\Delta$. A new…

Methodology · Statistics 2017-04-11 Hamza Dhaker , Papa Ngom , Malick Mbodj

We develop a new rank-based approach for univariate two-sample testing in the presence of missing data which makes no assumptions about the missingness mechanism. This approach is a theoretical extension of the Wilcoxon-Mann-Whitney test…

Methodology · Statistics 2024-03-25 Yijin Zeng , Niall M. Adams , Dean A. Bodenham

A two-sample hypothesis test is a statistical procedure used to determine whether the distributions generating two samples are identical. We consider the two-sample testing problem in a new scenario where the sample measurements (or sample…

Machine Learning · Computer Science 2024-07-01 Weizhi Li , Prad Kadambi , Pouria Saidi , Karthikeyan Natesan Ramamurthy , Gautam Dasarathy , Visar Berisha
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