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For a sequence $\{X_{n}, \, n \geqslant 1 \}$ of nonnegative random variables where $\max[\min(X_{n} - s,t),0]$, $t > s \geqslant 0$, satisfy a moment inequality, sufficient conditions are given under which $\sum_{k=1}^n (X_k - \mathbb{E}…

Probability · Mathematics 2020-11-23 João Lita da Silva

The purpose of this paper is to establish a general strong law of large numbers (SLLN) for arbitrary sequences of random variables (rv's) based on the squared indice method and to provide applications to SLLN of associated sequences. This…

Probability · Mathematics 2015-06-30 Harouna Sangare , Gane Samb Lo

We formulate and analyze a graphical model selection method for inferring the conditional independence graph of a high-dimensional nonstationary Gaussian random process (time series) from a finite-length observation. The observed process…

Machine Learning · Statistics 2016-09-14 Nguyen Tran Quang , Alexander Jung

We prove a martingale triangular array generalization of the Chow-Birnbaum-Marshall's inequality. The result is used to derive a strong law of large numbers for martingale triangular arrays whose rows are asymptotically stable in a certain…

Probability · Mathematics 2009-05-19 Yves F. Atchade

In terms of the Dirac representation of sample mean and the weak convergence of empirical distributions that holds almost surely, we construct a new proof for a strong law of large numbers of Kolmogorov's type with i.i.d. random variables…

Probability · Mathematics 2020-09-02 Yu-Lin Chou

This paper considers the problem of testing whether there exists a non-negative solution to a possibly under-determined system of linear equations with known coefficients. This hypothesis testing problem arises naturally in a number of…

Econometrics · Economics 2021-09-16 Zheng Fang , Andres Santos , Azeem M. Shaikh , Alexander Torgovitsky

This paper investigates conditional specifications for multivariate count variables. Recently, the spatial count data literature has proposed several conditional models such that the conditional expectations are linear in the conditioning…

Statistics Theory · Mathematics 2025-02-28 Yang Lu , Wei Sun

The aim of this note is to prove a law of large numbers for local patterns in discrete point processes. We investigate two different situations: a class of point processes on the one dimensional lattice including certain Schur measures, and…

Probability · Mathematics 2022-02-16 Pierre Lazag

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

A random variable (r.v.) X is said to follow Benford's law if log(X) is uniform mod 1. Many experimental data sets prove to follow an approximate version of it, and so do many mathematical series and continuous random variables. This…

Probability · Mathematics 2009-10-09 Nicolas Gauvrit , Jean-Paul Delahaye

We formulate nonparametric and semiparametric hypothesis testing of multivariate stationary linear time series in a unified fashion and propose new test statistics based on estimators of the spectral density matrix. The limiting…

Statistics Theory · Mathematics 2009-09-03 Yoshihiro Yajima , Yasumasa Matsuda

Derivations of two Bell's inequalities are given in a form appropriate to the interpretation of experimental data for explicit determination of all the correlations. They are arithmetic identities independent of statistical reasoning and…

Quantum Physics · Physics 2009-11-07 Louis Sica

It is shown that the Marcinkiewicz-Zygmund strong law of large numbers holds for pairwise independent identically distributed random variables. It is proved that if $X_{1}, X_{2}, \ldots$ are pairwise independent identically distributed…

Probability · Mathematics 2015-08-13 Valery Korchevsky

We consider dynamical systems on a finite measure space fulfilling a spectral gap property and Birkhoff sums of a non-negative, non-integrable observable. For such systems we generalize strong laws of large numbers for intermediately…

Dynamical Systems · Mathematics 2019-09-04 Marc Kesseböhmer , Tanja Schindler

We discuss a general method to construct correlated binomial distributions by imposing several consistent relations on the joint probability function. We obtain self-consistency relations for the conditional correlations and conditional…

Data Analysis, Statistics and Probability · Physics 2007-05-23 M. Hisakado , K. Kitsukawa , S. Mori

A classical problem of statistical inference is the valid specification of a model that can account for the statistical dependencies between observations when the true structure is dense, intractable, or unknown. To address this problem, a…

Statistics Theory · Mathematics 2023-10-19 Shane Sparkes , Lu Zhang

A general method to obtain strong laws of large numbers is studied. The method is based on abstract H\'ajek-R\'enyi type maximal inequalities. The rate of convergence in the law of large numbers is also considered. Some applications for…

Probability · Mathematics 2014-06-12 István Fazekas

In this paper, we derive limit laws for the empirical spectral distributions of random band and block matrices with correlated entries. In the first part of the paper, we study band matrices with approximately uncorrelated entries. We…

Probability · Mathematics 2022-02-11 Riccardo Catalano , Michael Fleermann , Werner Kirsch

We consider a population with non-overlapping generations, whose size goes to infinity. It is described by a discrete genealogy which may be time non-homogeneous and we pay special attention to branching trees in varying environments. A…

Probability · Mathematics 2013-05-22 Vincent Bansaye , Chunmao Huang

Maximal inequalities refer to bounds on expected values of the supremum of averages of random variables over a collection. They play a crucial role in the study of non-parametric and high-dimensional estimators, and especially in the study…

Probability · Mathematics 2025-04-28 Supratik Basu , Arun K Kuchibhotla
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