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We consider weighted sums of independent random variables regulated by an increment sequence. We provide operative conditions that ensure strong law of large numbers for such sums to hold in both the centered and non-centered case. The…

Probability · Mathematics 2021-03-11 Luca Avena , Conrado da Costa

Our aim is to give for some classes non-additive measures some limit theorems. For balanced games we obtain a weak and strong law of large numbers for bounded random variables, a sharper conclusion is obtain with exact games. We provide an…

Probability · Mathematics 2009-06-02 Yann Rebille

Let $f(n)$ be a strongly additive complex valued arithmetic function. Under mild conditions on $f$, we prove the following weighted strong law of large numbers: if $ X,X_1,X_2,... $ is any sequence of integrable i.i.d. random variables,…

Number Theory · Mathematics 2017-07-13 Istvan Berkes , Michel Weber

We formulate conditions for convergence of Laws of Large Numbers and show its links with of the parts of mathematical analysis such as summation theory, convergence of orthogonal series. We present also applications of the Law of Large…

Probability · Mathematics 2018-09-07 Paweł J. Szabłowski

Under the unifying umbrella of a general result of Penrose & Yukich [Ann. Appl. Probab., (2003) 13, 277--303] we give laws of large numbers (in the $L^p$ sense) for the total power-weighted length of several nearest-neighbour type graphs on…

Probability · Mathematics 2008-05-13 Andrew R. Wade

As the extension of uncorrelated single-valued random variables, set-valued case is studied in this paper. When the underlying space is of finite dimension, by using the support function, We shall prove the weak and strong laws of large…

Probability · Mathematics 2022-01-10 Li Guan , Jinping Zhang , Jieming Zhou

The problem of nearest neighbor condensing has enjoyed a long history of study, both in its theoretical and practical aspects. In this paper, we introduce the problem of weighted distance nearest neighbor condensing, where one assigns…

Machine Learning · Computer Science 2023-10-25 Lee-Ad Gottlieb , Timor Sharabi , Roi Weiss

In this paper, we study random walks evolving on Z in a dynamic random environment that we assume to have time correlations that decrease polynomially fast. We show a law of large numbers by generalizing methods already used for the…

Probability · Mathematics 2025-03-04 Julien Allasia

In this paper, we establish a new law of large numbers with the rate of convergence for special partial sums in a probability space. The proof relies on nonlinear expectation theory, as the uncertainty of random variables in the special…

Information Theory · Computer Science 2026-03-25 Jialiang Fu , Wen-Xuan Lang

A new version of a strong law of large numbers for a ``good'' pairwise independent sequence of random variables (r.v.'s) with a small part of ``bad'' dependent r.v.'s is proposed. The main goal is to relax the assumption on the existence of…

Probability · Mathematics 2025-06-10 I. V. Kozlov , A. Yu. Veretennikov

Let $X_1, \ldots, X_n$ be independent random points drawn from an absolutely continuous probability measure with density $f$ in $\mathbb{R}^d$. Under mild conditions on $f$, we derive a Poisson limit theorem for the number of large…

Probability · Mathematics 2018-11-20 László Györfi , Norbert Henze , Harro Walk

This note proves a law of large numbers for predicting several steps ahead, which, in the case of uniformly bounded random variables, generalizes the standard law of large numbers for martingales; the standard law of large numbers…

Probability · Mathematics 2026-04-14 Vladimir Vovk

Given $n$ independent random marked $d$-vectors (points) $X_i$ distributed with a common density, define the measure $\nu_n=\sum_i\xi_i$, where $\xi_i$ is a measure (not necessarily a point measure) which stabilizes; this means that $\xi_i$…

Statistics Theory · Mathematics 2009-09-29 Mathew D. Penrose

In this paper we obtain some possibilistic variants of the probabilistic laws of large numbers, different from those obtained by other authors, but very natural extensions of the corresponding ones in probability theory. Our results are…

Probability · Mathematics 2020-09-15 Sorin G. Gal

The main purpose of this paper is to obtain strong laws of large numbers for arrays or weighted sums of random variables under a scenario of dependence. Namely, for triangular arrays $\{X_{n,k}, \, 1 \leqslant k \leqslant n, \, n \geqslant…

Probability · Mathematics 2019-04-03 João Lita da Silva

In many empirical studies of a large two-sided matching market (such as in a college admissions problem), the researcher performs statistical inference under the assumption that they observe a random sample from a large matching market. In…

Econometrics · Economics 2024-04-02 Jacob Schwartz , Kyungchul Song

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

The article is devoted to the problem of calculating the probability density of a strictly stable law at $x\to\infty$. To solve this problem, it was proposed to use the expansion of the probability density in a power series. A…

Probability · Mathematics 2023-03-07 Viacheslav V. Saenko

We argue that the quantum probability law follows, in the large N limit, from the compatibility of quantum mechanics with classical-like properties of macroscopic objects. For a finite sample, we find that likely and unlikely measurement…

Quantum Physics · Physics 2009-11-07 Yakir Aharonov , Benni Reznik

We study the problem of recovering a collection of $n$ numbers from the evaluation of $m$ power sums. This yields a system of polynomial equations, which can be underconstrained ($m < n$), square ($m = n$), or overconstrained ($m > n$).…

Algebraic Geometry · Mathematics 2021-06-29 Hana Melánová , Bernd Sturmfels , Rosa Winter
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