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Related papers: Smoothed nonparametric tests and their properties

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Discrete kernel smoothing is now gaining importance in nonparametric statistics. In this paper, we investigate some asymptotic properties of the normalized discrete associated-kernel estimator of a probability mass function. We show, under…

Statistics Theory · Mathematics 2025-02-11 Youssef Esstafa , Célestin C. Kokonendji , Sobom M. Somé

This paper develops a novel nonparametric significance test based on a tailored nonparametric-type projected weighting function that exhibits appealing theoretical and numerical properties. We derive the asymptotic properties of the…

Econometrics · Economics 2026-02-18 Xiaojun Song , Jichao Yuan

Distribution-free tests such as the Wilcoxon rank sum test are popular for testing the equality of two univariate distributions. Among the important reasons for their popularity are the striking results of Hodges-Lehmann (1956) and…

Statistics Theory · Mathematics 2023-03-07 Nabarun Deb , Bhaswar B. Bhattacharya , Bodhisattva Sen

The change-plane Cox model is a popular tool for the subgroup analysis of survival data. Despite the rich literature on this model, there has been limited investigation into the asymptotic properties of the estimators of the…

Statistics Theory · Mathematics 2023-02-14 Shota Takeishi

We derive asymptotic expansions up to order $n^{-1/2}$ for the nonnull distribution functions of the likelihood ratio, Wald, score and gradient test statistics in the class of dispersion models, under a sequence of Pitman alternatives. The…

Statistics Theory · Mathematics 2011-02-23 Artur J. Lemonte , Silvia L. P. Ferrari

We establish higher-order nonasymptotic expansions for a difference between probability distributions of sums of i.i.d. random vectors in a Euclidean space. The derived bounds are uniform over two classes of sets: the set of all Euclidean…

Statistics Theory · Mathematics 2022-11-30 Mayya Zhilova

An important class of two-sample multivariate homogeneity tests is based on identifying differences between the distributions of interpoint distances. While generating distances from point clouds offers a straightforward and intuitive way…

Methodology · Statistics 2024-08-21 Annika Betken , Aljosa Marjanovic , Katharina Proksch

We propose a class of nonparametric two-sample tests with a cost linear in the sample size. Two tests are given, both based on an ensemble of distances between analytic functions representing each of the distributions. The first test uses…

Machine Learning · Statistics 2015-06-16 Kacper Chwialkowski , Aaditya Ramdas , Dino Sejdinovic , Arthur Gretton

Testing the equality in distributions of multiple samples is a common task in many fields. However, this problem for high-dimensional or non-Euclidean data has not been well explored. In this paper, we propose new nonparametric tests based…

Methodology · Statistics 2022-05-30 Hoseung Song , Hao Chen

We propose an exact nonparametric inference scheme for the detection of nonlinear determinism. The essential fact utilized in our scheme is that, for a linear stochastic process with jointly symmetric innovations, its ordinary least square…

Chaotic Dynamics · Physics 2007-05-23 Xiaodong Luo , Jie Zhang , Michael Small , Irene Moroz

The object of study is the problem of testing for uniformity of the multinomial distribution. We consider tests based on symmetric statistics, defined as the sum of some function of cell-frequencies. Mainly, attention is focused on the…

Statistics Theory · Mathematics 2022-09-12 Sherzod M. Mirakhmedov

The problem of curve registration appears in many different areas of applications ranging from neuroscience to road traffic modeling. In the present work, we propose a nonparametric testing framework in which we develop a generalized…

Statistics Theory · Mathematics 2015-02-20 Olivier Collier , Arnak S. Dalalyan

Randomized smoothing has shown promising certified robustness against adversaries in classification tasks. Despite such success with only zeroth-order access to base models, randomized smoothing has not been extended to a general form of…

Machine Learning · Computer Science 2024-05-16 Aref Miri Rekavandi , Olga Ohrimenko , Benjamin I. P. Rubinstein

This paper is concerned with testing normality in a Hilbert space based on the maximum mean discrepancy. Specifically, we discuss the behavior of the test from two standpoints: asymptotics and practical aspects. Asymptotic normality of the…

Statistics Theory · Mathematics 2019-02-12 Natsumi Makigusa , Kanta Naito

Given samples from two non-negative random variables, we propose a family of tests for the null hypothesis that one random variable stochastically dominates the other at the second order. Test statistics are obtained as functionals of the…

Statistics Theory · Mathematics 2023-10-16 Tommaso Lando , Sirio Legramanti

Various statistical tests have been developed for testing the equality of means in matched pairs with missing values. However, most existing methods are commonly based on certain distributional assumptions such as normality, 0-symmetry or…

Statistics Theory · Mathematics 2016-03-02 Lubna Amro , Markus Pauly

Standard tests of the "no-treatment-effect" hypothesis for a comparative experiment include permutation tests, the Wilcoxon rank sum test, two-sample $t$ tests, and Fisher-type randomization tests. Practitioners are aware that these…

Methodology · Statistics 2015-09-11 Joseph B. Lang

Classical two-sample permutation tests for equality of distributions have exact size in finite samples, but they fail to control size for testing equality of parameters that summarize each distribution. This paper proposes permutation tests…

Econometrics · Economics 2022-04-22 Marinho Bertanha , EunYi Chung

The notion of an e-value has been recently proposed as a possible alternative to critical regions and p-values in statistical hypothesis testing. In this paper we consider testing the nonparametric hypothesis of symmetry, introduce…

Statistics Theory · Mathematics 2024-01-29 Vladimir Vovk , Ruodu Wang

Based on the convex least-squares estimator, we propose two different procedures for testing convexity of a probability mass function supported on N with an unknown finite support. The procedures are shown to be asymptotically calibrated.

Statistics Theory · Mathematics 2017-01-17 Fadoua Balabdaoui , Cécile Durot , François Koladjo