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Neighborhood regression has been a successful approach in graphical and structural equation modeling, with applications to learning undirected and directed graphical models. We extend these ideas by defining and studying an algebraic…

Statistics Theory · Mathematics 2019-02-07 Arash A. Amini , Bryon Aragam , Qing Zhou

The paper studies the relationship between diffraction and dynamics for uniformly discrete ergodic point processes in real spaces. This relationship takes the form of an isometric embedding of two L^2 spaces. Diffraction (or equivalently…

Dynamical Systems · Mathematics 2009-11-13 Xinghua Deng , Robert V. Moody

We completely characterize $\Delta$- and local subexponentialities of positive-half compound Poisson distributions and extend the characterization on two-sided distributions. Moreover, $\Delta$-subexponentiality of infinitely divisible…

Probability · Mathematics 2023-02-21 Muneya Matsui , Toshiro Watanabe

A fundamental problem in statistics is measuring the correlation between two rankings of a set of items. Kendall's $\tau$ and Spearman's $\rho$ are well established correlation coefficients whose symmetric structure guarantees zero expected…

Methodology · Statistics 2026-03-03 Pierangelo Lombardo

Using the level--spacing distribution and the total probability function of the numbers of levels in a given energy interval we analyze the crossover of the level statistics between the delocalized and the localized regimes. By numerically…

Condensed Matter · Physics 2009-10-28 Isa Kh. Zharekeshev , Bernhard Kramer

In a bivariate setting, we consider the problem of detecting a sparse contamination or mixture component, where the effect manifests itself as a positive dependence between the variables, which are otherwise independent in the main…

Statistics Theory · Mathematics 2020-01-13 Ery Arias-Castro , Rong Huang , Nicolas Verzelen

We study the support (i.e. the set of visited sites) of a t step random walk on a two-dimensional square lattice in the large t limit. A broad class of global properties M(t) of the support is considered, including, e.g., the number S(t) of…

Condensed Matter · Physics 2007-05-23 F. van Wijland , S. Caser , H. J. Hilhorst

We investigate the two-points correlation function for several boundary-driven interacting particle systems. Our goal is to show that the time evolution of that correlation function is solution to a partial differential equation that can be…

Probability · Mathematics 2024-10-24 P. Gonçalves , B. Salvador

Conformal prediction has been a very popular method of distribution-free predictive inference in recent years in machine learning and statistics. Its popularity stems from the fact that it works as a wrapper around any prediction algorithm…

Methodology · Statistics 2021-06-07 Arun Kumar Kuchibhotla

Local correlation entropy, introduced by Takens in 1983, represents the exponential decay rate of the relative frequency of recurrences in the trajectory of a point, as the embedding dimension grows to infinity. In this paper we study…

Dynamical Systems · Mathematics 2021-12-09 Vladimír Špitalský

Statistical systems displaying a strongly anisotropic or dynamical scaling behaviour are characterized by an anisotropy exponent theta or a dynamical exponent z. For a given value of theta, we construct local scale transformations which can…

High Energy Physics - Theory · Physics 2015-06-26 Malte Henkel

We consider constraint-based methods for causal structure learning, such as the PC-, FCI-, RFCI- and CCD- algorithms (Spirtes et al. (2000, 1993), Richardson (1996), Colombo et al. (2012), Claassen et al. (2013)). The first step of all…

Machine Learning · Statistics 2013-09-30 Diego Colombo , Marloes H. Maathuis

Attribution modelling lies at the heart of marketing effectiveness, yet most existing approaches depend on user-level path data, which are increasingly inaccessible due to privacy regulations and platform restrictions. This paper introduces…

Machine Learning · Statistics 2025-12-25 Georgios Filippou , Boi Mai Quach , Diana Lenghel , Arthur White , Ashish Kumar Jha

Distance correlation is a recent extension of Pearson's correlation, that characterises general statistical independence between Euclidean-space-valued random variables, not only linear relations. This review delves into how and when…

Statistics Theory · Mathematics 2020-09-30 Fernando Castro-Prado , Wenceslao González-Manteiga

The paper discusses from a metaphysical standpoint the nature of the dependence relation underpinning the talk of mutual action between material and spatiotemporal structures in general relativity. It is shown that the standard analyses of…

History and Philosophy of Physics · Physics 2019-10-11 Antonio Vassallo

This paper focuses on a data-rich environment where the data set has a very large cross-sectional dimension, is likely to exhibit local dependence, and yet is hard to determine the dependence ordering. Such a situation arises, for example,…

Methodology · Statistics 2018-07-03 Kyungchul Song

Rank-based dependence measures such as Spearman's footrule are robust and invariant, but they often fail to capture directional or asymmetric dependence in multivariate settings. This paper introduces a new family of directional Spearman's…

Statistics Theory · Mathematics 2026-01-27 Enrique de Amo , David García-Fernández , Manuel Úbeda-Flores

We construct a 2-categorical extension of the relative entropy functor of Baez and Fritz, and show that our construction is functorial with respect to vertical morphisms. Moreover, we show such a `2-relative entropy' satisfies natural…

Information Theory · Computer Science 2022-01-19 James Fullwood

Exact regions between rank correlations describe the set of all pairs of values that two dependence measures can attain simultaneously on the same copula and thus yield sharp inequalities between them. In this paper, we determine the exact…

Statistics Theory · Mathematics 2026-03-11 Marcus Rockel

IIt is demonstrated that the entropy of statistical mechanics and of information theory, $S({\bf p}) = -\sum p_i \log p_i $ may be viewed as a measure of correlation. Given a probability distribution on two discrete variables, $p_{ij}$, we…

Mathematical Physics · Physics 2007-05-23 John H. Van Drie