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Given an input query, generative models such as large language models produce a random response drawn from a response distribution. Given two input queries, it is natural to ask if their response distributions are the same. While…

Statistics Theory · Mathematics 2025-09-16 Aranyak Acharyya , Carey E. Priebe , Hayden S. Helm

This article inspects whether a multivariate distribution is different from a specified distribution or not, and it also tests the equality of two multivariate distributions. In the course of this study, a graphical tool-kit using…

Methodology · Statistics 2024-08-19 Pratim Guha Niyogi , Subhra Sankar Dhar

Hypothesis test plays a key role in uncertain statistics based on uncertain measure. This paper extends the parametric hypothesis of a single uncertain population to multiple cases, thereby addressing a broader range of scenarios. First, an…

Methodology · Statistics 2025-12-03 Fan Zhang , Zhiming Li

We propose a new setting for testing properties of distributions while receiving samples from several distributions, but few samples per distribution. Given samples from $s$ distributions, $p_1, p_2, \ldots, p_s$, we design testers for the…

Data Structures and Algorithms · Computer Science 2019-11-19 Maryam Aliakbarpour , Sandeep Silwal

Permutation tests are a distribution free way of performing hypothesis tests. These tests rely on the condition that the observed data are exchangeable among the groups being tested under the null hypothesis. This assumption is easily…

Methodology · Statistics 2017-12-14 Daniell Toth

We provide a distribution-free test that can be used to determine whether any two joint distributions $p$ and $q$ are statistically different by inspection of a large enough set of samples. Following recent efforts from Long et al. [1], we…

Machine Learning · Computer Science 2016-07-26 Francesco Solera , Andrea Palazzi

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

An exact computation of the persistent Betti numbers of a submanifold $X$ of a Euclidean space is possible only in a theoretical setting. In practical situations, only a finite sample of $X$ is available. We show that, under suitable…

Algebraic Topology · Mathematics 2015-07-21 Niccolò Cavazza , Massimo Ferri , Claudia Landi

In this article, we present a nonparametric method for the general two-sample problem involving functional random variables modelled as elements of a separable Hilbert space ${\cal H}$. First, we present a general recipe based on linear…

Methodology · Statistics 2024-10-08 Bilol Banerjee

We consider testing equivalence to Hardy-Weinberg Equilibrium in case of multiple alleles. Two different test statistics are proposed for this test problem. The asymptotic distribution of the test statistics is derived. The corresponding…

Methodology · Statistics 2025-07-15 Vladimir Ostrovski

Persistent homology is a vital tool for topological data analysis. Previous work has developed some statistical estimators for characteristics of collections of persistence diagrams. However, tools that provide statistical inference for…

Applications · Statistics 2016-02-23 Andrew Robinson , Katharine Turner

Experiments often yield non-identically distributed data for statistical analysis. Tests of hypothesis under such set-ups are generally performed using the likelihood ratio test, which is non-robust with respect to outliers and model…

Statistics Theory · Mathematics 2017-07-25 Abhik Ghosh , Ayanendranath Basu

Persistent homology is a multiscale method for analyzing the shape of sets and functions from point cloud data arising from an unknown distribution supported on those sets. When the size of the sample is large, direct computation of the…

In the classical two-sample problem, the conventional approach for testing distributions equality is based on the difference between the two marginal empirical distribution functions, whereas a test for independence is based on the contrast…

Statistics Theory · Mathematics 2018-06-14 Laura Dumitrescu , Estate V. Khmaladze

We examine the extent to which sublinear-sample property testing and estimation apply to settings where samples are independently but not identically distributed. Specifically, we consider the following distributional property testing…

Data Structures and Algorithms · Computer Science 2025-11-05 Shivam Garg , Chirag Pabbaraju , Kirankumar Shiragur , Gregory Valiant

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

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

The predictions of mean-field electrodynamics can now be probed using direct numerical simulations of random flows and magnetic fields. When modelling astrophysical MHD, it is important to verify that such simulations are in agreement with…

Data Analysis, Statistics and Probability · Physics 2018-09-12 Irina Makarenko , Paul Bushby , Andrew Fletcher , Robin Henderson , Nikolay Makarenko , Anvar Shukurov

Two-sample hypothesis testing for random graphs arises naturally in neuroscience, social networks, and machine learning. In this paper, we consider a semiparametric problem of two-sample hypothesis testing for a class of latent position…

Methodology · Statistics 2015-06-19 Minh Tang , Avanti Athreya , Daniel L. Sussman , Vince Lyzinski , Carey E. Priebe

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