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In this article, we study the test for independence of two random elements $X$ and $Y$ lying in an infinite dimensional space ${\cal{H}}$ (specifically, a real separable Hilbert space equipped with the inner product $\langle .,…

Statistics Theory · Mathematics 2024-10-15 Suprio Bhar , Subhra Sankar Dhar

The lack of evidence in favor of any new physics models means that the search for new physics beyond the Standard Model (BSM) is wide open, with no direction clearly more promising than any other. This marks a turn towards what can be…

History and Philosophy of Physics · Physics 2025-07-08 Martin King

In this paper we introduce a new measure of conditional dependence between two random vectors ${\boldsymbol X}$ and ${\boldsymbol Y}$ given another random vector $\boldsymbol Z$ using the ball divergence. Our measure characterizes…

Statistics Theory · Mathematics 2024-08-01 Bilol Banerjee , Bhaswar B. Bhattacharya , Anil K. Ghosh

Testing the independence between random vectors is a fundamental problem in statistics. Distance correlation, a recently popular dependence measure, is universally consistent for testing independence against all distributions with finite…

Methodology · Statistics 2024-08-22 Yuwei Ke , Hok Kan Ling , Yanglei Song

We propose a class of flexible non-parametric tests for the presence of dependence between components of a random vector based on weighted Cram\'{e}r-von Mises functionals of the empirical copula process. The weights act as a tuning…

Statistics Theory · Mathematics 2014-05-29 Ivan Medovikov

Relying on some auxiliary assumptions, usually considered mild, Bell's theorem proves that no local theory can reproduce all the predictions of quantum mechanics. In this work, we introduce a fully local, superdeterministic model that, by…

Quantum Physics · Physics 2020-08-04 G. S. Ciepielewski , E. Okon , D. Sudarsky

This course introduces the fruitful links between model theory and a combinatoric of sets given by independence relations. An independence relation on a set is a ternary relation between subsets. Chapter 1 should be considered as an…

Logic · Mathematics 2025-01-28 Christian d'Elbée

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

It is shown that the ability of the interval probability representation to capture epistemological independence is severely limited. Two events are epistemologically independent if knowledge of the first event does not alter belief (i.e.,…

Artificial Intelligence · Computer Science 2013-02-18 Lonnie Chrisman

We introduce a new information-theoretic formulation of quantum measurement uncertainty relations, based on the notion of relative entropy between measurement probabilities. In the case of a finite-dimensional system and for any approximate…

Mathematical Physics · Physics 2018-03-02 Alberto Barchielli , Matteo Gregoratti , Alessandro Toigo

Metric spaces are a fundamental component of mathematics and have a paramount importance as a framework for measuring distance. They can be found in many different branches of mathematics, such as analysis and topology. This paper offers an…

General Topology · Mathematics 2025-10-30 Ismail Gemaledin , Iusuf Gemaledin

Testing for pairwise independence for the case where the number of variables may be of the same size or even larger than the sample size has received increasing attention in the recent years. We contribute to this branch of the literature…

Statistics Theory · Mathematics 2024-09-18 Axel Bücher , Cambyse Pakzad

The representation of independence relations generally builds upon the well-known semigraphoid axioms of independence. Recently, a representation has been proposed that captures a set of dominant statements of an independence relation from…

Artificial Intelligence · Computer Science 2012-07-19 Peter de Waal , Linda C. van der Gaag

We initiate a systematic investigation of the abstract elementary classes that have amalgamation, satisfy tameness (a locality property for orbital types), and are stable (in terms of the number of orbital types) in some cardinal. Assuming…

Logic · Mathematics 2018-11-22 Sebastien Vasey

Dependence strucuture estimation is one of the important problems in machine learning domain and has many applications in different scientific areas. In this paper, a theoretical framework for such estimation based on copula and copula…

Machine Learning · Computer Science 2019-09-11 Jian Ma , Zengqi Sun

This paper has three parts. First, we study and characterize amenable and extremely amenable topological semigroups in terms of invariant measures using integral logic. We prove definability of some properties of a topological semigroup…

Logic · Mathematics 2016-07-12 Karim Khanaki

We investigate the role of a statistical complexity measure to assign equilibration in isolated quantum systems. While unitary dynamics preserve global purity, expectation values of observables often exhibit equilibration-like behavior,…

Quantum Physics · Physics 2025-08-14 Marcos G. Alpino , Tiago Debarba , Reinaldo O. Vianna , André T. Cesário

Recently it has been argued that entropy can be a direct measure of complexity, where the smaller value of entropy indicates lower system complexity, while its larger value indicates higher system complexity. We dispute this view and…

Statistical Mechanics · Physics 2020-08-26 Jarosław Klamut , Ryszard Kutner , Zbigniew R. Struzik

Indeterminacy associated with probing of a quantum state is commonly expressed through spectral distances (metric) featured in the outcomes of repeated experiments. Here we express it as an effective amount (measure) of distinct outcomes…

Quantum Physics · Physics 2021-09-21 Ivan Horváth

We develop inference procedures robust to general forms of weak dependence. The procedures utilize test statistics constructed by resampling in a manner that does not depend on the unknown correlation structure of the data. We prove that…

Econometrics · Economics 2021-08-26 Michael P. Leung
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