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Permanents of random matrices with independent and identically distributed (i.i.d.) entries have extensively studied in literature and convergence and concentration properties are known under varying assumptions on the distributions. In…

Probability · Mathematics 2021-12-13 Ghurumuruhan Ganesan

We extend to the multilinear setting classical inequalities of Marcinkiewicz and Zygmund on $\ell^r$-valued extensions of linear operators. We show that for certain $1 \leq p, q_1, \dots, q_m, r \leq \infty$, there is a constant $C\geq 0$…

Functional Analysis · Mathematics 2017-08-31 Daniel Carando , Martin Mazzitelli , Sheldy Ombrosi

A critical branching process $\left\{Z_{k},k=0,1,2,...\right\} $ in a random environment generated by a sequence of independent and identically distributed random reproduction laws is considered.\ Let $Z_{p,n}$ be the number of particles at…

Probability · Mathematics 2016-08-30 V. A. Vatutin , E. E. Dyakonova

For a strictly stationary sequence of random variables we derive functional convergence of the joint partial sum and partial maxima process under joint regular variation with index $\alpha \in (0,2)$ and weak dependence conditions. The…

Probability · Mathematics 2019-10-08 Danijel Krizmanic

(English) This monograph aims at presenting the core weak convergence theory for sequences of random vectors with values in $\mathbb{R}^k$. In some places, a more general formulation in metric spaces is provided. It lays out the necessary…

Probability · Mathematics 2018-08-09 Gane Samb Lo , Modou Ngom , Tchilabalo Atozou Kpanzou

In this paper, we expand and generalize the findings presented in our previous work on the law of large numbers and the large deviation principle for Poisson processes with uniform catastrophes. We study three distinct scalings: sublinear…

Probability · Mathematics 2025-05-29 A. Logachov , O. Logachova , A. Yambartsev

In this paper we prove a strong law of large numbers and its L^1-convergence counterpart for the process counted with a random characteristic in the context of self-similar fragmentation processes. This result extends a somewhat analogical…

Probability · Mathematics 2012-03-20 Robert Knobloch

The arm of this paper is to establish the strong law of large numbers (SLLN) of $m$-dependent random variables under the framework of sub-linear expectations. We establish the SLLN for a sequence of independent, but not necessarily…

Probability · Mathematics 2024-04-02 Wang-Yun Gu , Li-Xin Zhang

We continue our study of the distribution of the maximal number $X^{\ast}_k$ of offsprings amongst all individuals in a critical Galton-Watson process started with $k$ ancestors, treating the case when the reproduction law has a regularly…

Probability · Mathematics 2012-09-19 Jean Bertoin

We establish a strong law of large numbers for one-dimensional continuous-time random walks in dynamic random environments under two main assumptions: the environment is required to satisfy a decoupling inequality that can be interpreted as…

Probability · Mathematics 2023-11-22 Weberson S. Arcanjo , Rangel Baldasso , Marcelo R. Hilário , Renato S. dos Santos

For 1<p< \infty, weight w \in A_p, and any L ^2 -bounded Calder\'on-Zygmund operator T, we show that there is a constant C(T,P) so that we prove the sharp norm dependence on T_#, the maximal truncations of T, in both weak and strong type…

The availability of large datasets requires an improved view on statistical laws in complex systems, such as Zipf's law of word frequencies, the Gutenberg-Richter law of earthquake magnitudes, or scale-free degree distribution in networks.…

Data Analysis, Statistics and Probability · Physics 2019-04-30 Martin Gerlach , Eduardo G. Altmann

We establish optimal logarithmic rates of convergence in the strong invariance principle for multivariate cumulative processes in the Smith's sense. Exponential probabilistic inequalities of Koml\'{o}s-Major-Tusn\'{a}dy type are obtained.…

Probability · Mathematics 2020-06-18 Elena Bashtova , Alexey Shashkin

This work is devoted to averaging principle of a two-time-scale stochastic partial differential equation on a bounded interval $[0, l]$, where both the fast and slow components are directly perturbed by additive noises. Under some regular…

Probability · Mathematics 2018-02-06 Hongbo Fu , Li Wan , Jicheng Liu , Xianming Liu

The purpose of this paper is to study the approximation of vector valued mappings defined on a subset of a normed space. We investigate Korovkin-type conditions under which a given sequence of linear operators becomes a so-called…

Functional Analysis · Mathematics 2007-05-23 Lorenzo D'Ambrosio

We consider the behavior of extremal particles in $K$-symmetric exclusion on $\mathbb{Z}$ when the process starts from certain infinite-particle step configurations where there are no particles to the right of a maximal one. In such a…

Probability · Mathematics 2025-06-17 Michael Conroy , Adrián González Casanova , Sunder Sethuraman

One of the main differences between the central limit theorem and the Poisson law of small numbers is that the former possesses the large sample property (LSP), i.e., the error of normal approximation to the sum of $n$ independent…

Probability · Mathematics 2019-06-25 Tianshu Cong , Aihua Xia , Fuxi Zhang

We consider a class of slow-fast processes on a connected complete Riemannian manifold $M$.The limiting dynamics as the scale separation goes to $\infty$ is governed by the averaging principle. Around this limit, we prove large deviation…

Probability · Mathematics 2024-03-11 Yanyan Hu , Richard C. Kraaij , Fubao Xi

Let $(X_k)_{k\geq 1}$ and $(Y_k)_{k\geq 1}$ be two independent sequences of i.i.d. random variables, with values in a finite and totally ordered alphabet $\mathcal{A}_m:=\{1,\dots,m\}$, and having respective probability mass function…

Probability · Mathematics 2021-04-13 Clément Deslandes , Christian Houdré

A statistical model of discrete finite length random processes with negative power law spectral densities is presented. The definition of terms is followed by a description of the spectral density trend. An algorithmic construction of…

Instrumentation and Methods for Astrophysics · Physics 2023-02-13 Robert Kimberk , Keara Carter , Todd Hunter