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Conditional independence and graphical models are well studied for probability distributions on product spaces. We propose a new notion of conditional independence for any measure $\Lambda$ on the punctured Euclidean space $\mathbb…

Statistics Theory · Mathematics 2024-09-12 Sebastian Engelke , Jevgenijs Ivanovs , Kirstin Strokorb

We show that a form of dependence known as G-dependence (originally introduced by Grelling) admits a very natural finite axiomatization, as well as Armstrong relations. We also give an explicit translation between functional dependence and…

Logic · Mathematics 2018-02-20 Gianluca Paolini

We study idempotent measures and the structure of the convolution semigroups of measures over definable groups. We isolate the property of generic transitivity and demonstrate that it is sufficient (and necessary) to develop stable group…

Logic · Mathematics 2025-04-08 Artem Chernikov , Kyle Gannon , Krzysztof Krupiński

Spherical and hyperspherical data are commonly encountered in diverse applied research domains, underscoring the vital task of assessing independence within such data structures. In this context, we investigate the properties of test…

Methodology · Statistics 2024-01-23 Marija Cuparić , Bruno Ebner , Bojana Milošević

Conditional independence, and more generally conditional mutual independence, are central notions in probability theory. In their general forms, they include functional dependence as a special case. In this paper, we tackle two fundamental…

Probability · Mathematics 2026-03-24 Laigang Guo , Raymond W. Yeung , Tao Guo

Mathematical models are sometime given as functions of independent input variables and equations or inequations connecting the input variables. A probabilistic characterization of such models results in treating them as functions with…

Optimization and Control · Mathematics 2023-04-13 Matieyendou Lamboni

Measuring conditional dependence is an important topic in statistics with broad applications including graphical models. Under a factor model setting, a new conditional dependence measure based on projection is proposed. The corresponding…

Methodology · Statistics 2019-01-14 Jianqing Fan , Yang Feng , Lucy Xia

Possibilistic conditional independence is investigated: we propose a definition of this notion similar to the one used in probability theory. The links between independence and non-interactivity are investigated, and properties of these…

Artificial Intelligence · Computer Science 2013-02-28 Pascale Fonck

This Comment argues that two assumptions, which are presented as basic assumptions of Bell's theorem in [J. Handsteiner et al., Phys. Rev. Lett. 118, 060401 (2017)] and elsewhere, in fact follow from more basic premises. Measurement…

Quantum Physics · Physics 2017-05-12 Nathan Argaman

We develop a fine-scale local analysis of measure entropy and measure sequence entropy based on combinatorial independence. The concepts of measure IE-tuples and measure IN-tuples are introduced and studied in analogy with their…

Dynamical Systems · Mathematics 2007-05-24 David Kerr , Hanfeng Li

We study some dynamical aspects of the action of automorphisms in model theory in particular in the presence of invariant measures. We give some characterizations for NIP theories in terms of dynamics of automorphisms and invariant measures…

Logic · Mathematics 2022-12-19 Alireza Mofidi

In this paper, we characterize several classes of continuous radial basis functions that can be employed to determine whether a interaction of a probability is zero or not. These functions encompass standard independence tests but also the…

Classical Analysis and ODEs · Mathematics 2024-07-10 Jean Carlo Guella

Based on recent progress in research on copula based dependence measures, we review the original Renyi's axioms on symmetric measures and propose a new set of axioms that applies to nonsymmetric measures. We show that nonsymmetric measures…

Methodology · Statistics 2015-02-16 Hui Li

Two families of dependence measures between random variables are introduced. They are based on the R\'enyi divergence of order $\alpha$ and the relative $\alpha$-entropy, respectively, and both dependence measures reduce to Shannon's mutual…

Information Theory · Computer Science 2019-08-22 Amos Lapidoth , Christoph Pfister

Measuring a strength of dependence of random variables is an important problem in statistical practice. In this paper, we propose a new function valued measure of dependence of two random variables. It allows one to study and visualize…

Methodology · Statistics 2014-05-12 Teresa Ledwina

The Glivenko--Cantelli theorem is a uniform version of the strong law of large numbers. It states that for every IID sequence of random variables, the empirical measure converges to the underlying distribution (in the sense of uniform…

Probability · Mathematics 2026-05-13 Tobias Fritz , Tomáš Gonda , Antonio Lorenzin , Paolo Perrone , Areeb Shah Mohammed

A recent article of Chernikov, Hrushovski, Kruckman, Krupinski, Moconja, Pillay and Ramsey finds the first examples of simple structures with formulas which do not fork over $\emptyset$ but are universally measure zero. In this article we…

Logic · Mathematics 2025-08-26 Paolo Marimon

We develop a framework, in the style of Adler, for interpreting the notion of "witnessing" that has appeared (usually as a variant of Kim's Lemma) in different areas of neostability theory as a binary relation between abstract independence…

Logic · Mathematics 2026-02-20 Alberto Miguel-Gómez

In this paper we extend Fischler's quantitative generalization of Nesterenko's linear independence criterion, by weakening the hypotheses on the divisors of the coe cients of the linear forms and allowing (to some extent) the linear forms…

Number Theory · Mathematics 2014-03-18 Simon Dauguet

The multiple testing literature has primarily dealt with three types of dependence assumptions between p-values: independence, positive regression dependence, and arbitrary dependence. In this paper, we provide what we believe are the first…

Statistics Theory · Mathematics 2024-05-10 Ziyu Chi , Aaditya Ramdas , Ruodu Wang
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