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In this paper,under an abstract setting we establish the existence of spatially inhomogeneous steady states and the asymptotic propagation properties for a large class of monotone evolution systems without spatial translation invariance.…

Analysis of PDEs · Mathematics 2020-07-09 Taishan Yi , Xiao-Qiang Zhao

We propose a new class of models for random permutations, which we call log-linear models, by the analogy with log-linear models used in the analysis of contingency tables. As a special case, we study the family of all Luce-decomposable…

Statistics Theory · Mathematics 2007-11-19 V. Csiszár

Let $\mathbf{X}(n) \in \mathbb{R}^d$ be a sequence of random vectors, where $n\in\mathbb{N}$ and $d = d(n)$. Under certain weakly dependence conditions, we prove that the distribution of the maximal component of $\mathbf{X}$ and the…

Probability · Mathematics 2025-04-22 Mikhail Isaev , Igor Rodionov , Rui-Ray Zhang , Maksim Zhukovskii

We study the ergodic and statistical properties of a class of maps of the circle and of the interval of Lorenz type which present indifferent fixed points and points with unbounded derivative. These maps have been previously investigated in…

Dynamical Systems · Mathematics 2008-12-16 Giampaolo Cristadoro , Nicolai Haydn , Philippe Marie , Sandro Vaienti

We develop a theory of formal multivariate polynomials over commutative rings by treating them as ring terms. Our main result is that two ring terms are s-equivalent (when expanded they yield the same standard polynomial) iff they are…

Combinatorics · Mathematics 2024-01-30 M. Klazar

We propose two model-free, permutation-based tests of independence between a pair of random variables. The tests can be applied to samples from any bivariate distribution: continuous, discrete or mixture of those, with light tails or heavy…

Methodology · Statistics 2022-05-16 Jiří Dvořák , Tomáš Mrkvička

We consider a nonparametric Bayesian approach to estimation and testing for a multivariate monotone density. Instead of following the conventional Bayesian route of putting a prior distribution complying with the monotonicity restriction,…

Statistics Theory · Mathematics 2023-06-09 Kang Wang , Subhashis Ghosal

Voiculescu's notion of asymptotic free independence is known for a large class of random matrices including independent unitary invariant matrices. This notion is extended for independent random matrices invariant in law by conjugation by…

Probability · Mathematics 2018-03-09 Camille Male

It is known that if X is uniformly distributed modulo 1 and Y is an arbitrary random variable independent of X then Y+X is also uniformly distributed modulo 1. We prove a converse for any continuous random variable Y (or a reasonable…

Probability · Mathematics 2013-07-16 Michał Ryszard Wójcik

This note examines the infinite divisibility of density-based transformations of normal random variables. We characterize a class of density-based transformations of normal variables which produces non-infinitely divisible distributions. We…

Statistics Theory · Mathematics 2011-08-03 A. Murillo-Salas , F. J. Rubio

The de Finetti representation theorem for continuous variable quantum system is first developed to approximate an N-partite continuous variable quantum state with a convex combination of independent and identical subsystems, which requires…

Quantum Physics · Physics 2016-09-28 Murphy Yuezhen Niu

The article treats the geometrical theory of partial differential equations in the absolute sense, i.e., without any additional structures and especially without any preferred choice of independent and dependent variables. The equations are…

Differential Geometry · Mathematics 2014-01-14 Veronika Chrastinová , Václav Tryhuk

We say that $f:[0,1]\to [0,1]$ is a {\it piecewise continuous interval map} if there exists a partition $0=x_0<x_1<\cdots<x_{d}<x_{d+1}=1$ of $[0,1]$ such that $f\vert_{(x_{i-1},x_i)}$ is continuous and the lateral limits $w_0^+=\lim_{x\to…

Dynamical Systems · Mathematics 2016-03-09 Benito Pires

We propose a new conditional dependence measure and a statistical test for conditional independence. The measure is based on the difference between analytic kernel embeddings of two well-suited distributions evaluated at a finite set of…

Machine Learning · Statistics 2022-06-17 Meyer Scetbon , Laurent Meunier , Yaniv Romano

In this paper we present a conditional principle of Gibbs type for independent nonidentically distributed random vectors. We obtain this result by performing Edgeworth expansions for densities of sums of independent random vectors.

Probability · Mathematics 2022-01-19 Dimbihery Rabenoro

Tests of independence are an important tool in applications, specifically in connection with the detection of a relationship between variables; they also have initiated many developments in statistical theory. In the present paper we build…

Statistics Theory · Mathematics 2026-05-13 L. Baringhaus , R. Grübel

In this work, we consider an extension of graphical models to random graphs, trees, and other objects. To do this, many fundamental concepts for multivariate random variables (e.g., marginal variables, Gibbs distribution, Markov properties)…

Machine Learning · Statistics 2017-05-08 Neil Hallonquist

In this article we investigate different forms of multiplicative independence between the sequences $n$ and $\lfloor n \alpha \rfloor$ for irrational $\alpha$. Our main theorem shows that for a large class of arithmetic functions $a, b…

Number Theory · Mathematics 2023-12-08 David Crnčević , Felipe Hernández , Kevin Rizk , Khunpob Sereesuchart , Ran Tao

It is shown that every conditional spreading sequence can be decomposed into two well behaved parts, one being unconditional and the other being convex block homogeneous, i.e. equivalent to its convex block sequences. This decomposition is…

Functional Analysis · Mathematics 2016-11-15 Spiros A. Argyros , Pavlos Motakis , Bünyamin Sari

We extend de Finetti's (1937) notion of exchangeability to finite and countable sequences of variables, when a subject's beliefs about them are modelled using coherent lower previsions rather than (linear) previsions. We prove…

Probability · Mathematics 2008-01-09 Gert de Cooman , Erik Quaeghebeur , Enrique Miranda
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