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Nonparametric two sample testing is a decision theoretic problem that involves identifying differences between two random variables without making parametric assumptions about their underlying distributions. We refer to the most common…

Statistics Theory · Mathematics 2015-08-05 Aaditya Ramdas , Sashank J. Reddi , Barnabas Poczos , Aarti Singh , Larry Wasserman

We use the notion of topological data analysis to compare metrics on data sets. We provide two different motivating examples for this. The first of these is a point cloud data set that has $\mathbb{R}^2$ as its ambient space, and is…

General Topology · Mathematics 2015-03-17 Scott Balchin , Etienne Pillin

This paper concerns a method of testing equality of distribution of random convex compact sets and the way how to use the test to distinguish between two realisations of general random sets. The family of metrics on the space of…

Statistics Theory · Mathematics 2018-01-09 Vesna Gotovac , Kateřina Helisová

A classical question about a metric space is whether Borel measures on the space are determined by their values on balls. We show that for any given measure this property is stable under Gromov-Wasserstein convergence of metric measure…

Algebraic Topology · Mathematics 2024-01-23 Anne van Delft , Andrew J. Blumberg

Non-parametric two-sample tests based on energy distance or maximum mean discrepancy are widely used statistical tests for comparing multivariate data from two populations. While these tests enjoy desirable statistical properties, their…

Computation · Statistics 2024-06-11 Elias Chaibub Neto

Traditional applications of latent class models (LCMs) often focus on scenarios where a set of unobserved classes are well-defined and easily distinguishable. However, in numerous real-world applications, these classes are weakly separated…

Computation · Statistics 2023-09-21 Mengbing Li , Bolin Wu , Briana Stephenson , Zhenke Wu

Testing mutual independence among multiple random variables is a fundamental problem in statistics, with wide applications in genomics, finance, and neuroscience. In this paper, we propose a new class of tests for high-dimensional mutual…

Applications · Statistics 2026-01-28 Ping Zhao , Huifang Ma

Independence analysis is an indispensable step before regression analysis to find out essential factors that influence the objects. With many applications in machine Learning, medical Learning and a variety of disciplines, statistical…

Methodology · Statistics 2022-07-08 Wenliang Pan , Yujue Li , Jianwu Liu , Pei Dang , Weixiong Mai

Recent literature has shown that symbolic data, such as text and graphs, is often better represented by points on a curved manifold, rather than in Euclidean space. However, geometrical operations on manifolds are generally more complicated…

Machine Learning · Computer Science 2019-02-06 Max Aalto , Nakul Verma

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…

Mapper and Ball Mapper are Topological Data Analysis tools used for exploring high dimensional point clouds and visualizing scalar-valued functions on those point clouds. Inspired by open questions in knot theory, new features are added to…

Algebraic Topology · Mathematics 2023-03-29 Paweł Dłotko , Davide Gurnari , Radmila Sazdanovic

In this paper we describe simode: Separable Integral Matching for Ordinary Differential Equations. The statistical methodologies applied in the package focus on several minimization procedures of an integral-matching criterion function,…

Computation · Statistics 2018-10-09 Rami Yaari , Itai Dattner

A consistent theme in software experimentation at Microsoft has been solving problems of experimentation at scale for a diverse set of products. Running experiments at scale (i.e., many experiments on many users) has become state of the art…

Applications · Statistics 2019-12-03 Craig Boucher , Ulf Knoblich , Daniel Miller , Sasha Patotski , Amin Saied , Venky Venkateshaiah

Measurement error and missing data in variables used in statistical models are common, and can at worst lead to serious biases in analyses if they are ignored. Yet, these problems are often not dealt with adequately, presumably in part…

Methodology · Statistics 2024-06-13 Emma Skarstein , Stefanie Muff

We propose a simple and intuitive test for arguably the most prevailing hypothesis in statistics that data are independent and identically distributed (IID), based on a newly introduced off-diagonal sequential U-process. This IID test is…

Methodology · Statistics 2025-06-30 Tongyu Li , Jonas Mueller , Fang Yao

The synthpop package for R https://www.synthpop.org.uk provides tools to allow data custodians to create synthetic versions of confidential microdata that can be distributed with fewer restrictions than the original. The synthesis can be…

Computation · Statistics 2021-11-16 Gillian M Raab , Beata Nowok , Chris Dibben

BDSAR is an R package which estimates distances between probability distributions and facilitates a dynamic and powerful analysis of diagnostics for Bayesian models from the class of Simultaneous Autoregressive (SAR) spatial models. The…

Computation · Statistics 2017-04-26 Ian M Danilevicz , Ricardo S Ehlers

The statistics of gap ratios between consecutive energy levels is a widely used tool, in particular in the context of many-body physics, to distinguish between chaotic and integrable systems, described respectively by Gaussian ensembles of…

Disordered Systems and Neural Networks · Physics 2022-02-28 Olivier Giraud , Nicolas Macé , Eric Vernier , Fabien Alet

This paper presents a procedure for testing the hypothesis that the underlying distribution of the data is elliptical when using robust location and scatter estimators instead of the sample mean and covariance matrix. Under mild assumptions…

Methodology · Statistics 2015-02-20 Ana M. Bianco , Graciela Boente , Isabel M. Rodrigues

In this paper we use a well know method in statistics, the $\delta$-method, to provide an asymptotic distribution for the Mutual Information, and construct and independence test based on it. Interesting connections are found with the…

Methodology · Statistics 2025-02-26 Marius Marinescu , Costel Balcau
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