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The Rotar central limit theorem is a remarkable theorem in the non-classical version since it does not use the condition of asymptotic infinitesimality for the independent individual summands, unlike the theorems named Lindeberg's and…

Probability · Mathematics 2023-09-26 Tran Loc Hung

Let $K$ be a smooth convex set with volume one in $\BBR^d$. Choose $n$ random points in $K$ independently according to the uniform distribution. The convex hull of these points, denoted by $K_n$, is called a {\it random polytope}. We prove…

Probability · Mathematics 2007-05-23 Van Vu

We investigate a functional obtained by summing the squared differences of the integral of an Ito process over disjoint intervals. The limit of this sum is shown to converge in probability to two thirds the quadratic variation of the…

Probability · Mathematics 2013-08-14 John F. A. Fletcher

Sum rules are elegant formulas that relate entropy functionals to coefficients associated with orthogonal polynomials [Sim11]. In a series of paper (see for example [GNR16], [GNR17], [BSZ18a], [BSZ18b]), interesting connections have been…

Probability · Mathematics 2025-10-20 Fabrice Gamboa , Jan Nagel , Alain Rouault

The random polytope $K_n$, defined as the convex hull of $n$ points chosen uniformly at random on the boundary of a smooth convex body, is considered. Proofs for lower and upper variance bounds, strong laws of large numbers and central…

Probability · Mathematics 2017-06-12 Nicola Turchi , Florian Wespi

Let $X,X_1,\ldots,X_n$ be independent identically distributed random variables. The paper deals with the question about the behavior of the concentration function of the random variable $\sum\limits_{k=1}^{n}X_k a_k$ according to the…

Probability · Mathematics 2013-03-19 Yu. S. Eliseeva

This paper proves several weak limit theorems for the joint version of extreme order statistics and partial sums of independently and identically distributed random variables. The results are also extended to almost sure limit version.

Probability · Mathematics 2023-12-18 Gaoyu Li , Zhongquan Tan

We provide non-asymptotic bounds and asymptotic limits for convex transport costs between the distribution of partial sums of independent and identically distributed square integrable and centered random variables and the normal…

Probability · Mathematics 2026-03-03 Jérôme Dedecker , Florence Merlevède , Emmanuel Rio

A sum rule is an identity connecting the entropy of a measure with coefficients involved in the construction of its orthogonal polynomials (Jacobi coefficients). Our paper is an extension of Gamboa, Nagel and Rouault (2016), where we have…

Probability · Mathematics 2020-04-29 Fabrice Gamboa , Jan Nagel , Alain Rouault

Limit theorems for a random number of independent random variables are frequently called transfer theorems. Investigations into this direction for sums of random variables with independent random sample size have been originated by…

Probability · Mathematics 2016-03-14 Peter Kern

It is shown that at least 50% of the probability mass of a sum of independent Rademacher random variables is within one standard deviation from its mean. This lower bound is sharp, it is much better than for instance the bound that can be…

Probability · Mathematics 2011-12-22 Martien C. A. van Zuijlen

In this note, we study inequality and limit theory under sublinear expectations. We mainly prove Doob's inequality for submartingale and Kolmogrov's inequality. By Kolmogrov's inequality, we obtain a special version of Kolmogrov's law of…

Probability · Mathematics 2015-06-19 Ze-Chun Hu , Yan-Zhi Yang

This paper derives a new strong Gaussian approximation bound for the sum of independent random vectors. The approach relies on the optimal transport theory and yields \textit{explicit} dependence on the dimension size $p$ and the sample…

Statistics Theory · Mathematics 2021-09-06 Nazar Buzun , Nikolay Shvetsov , Dmitry V. Dylov

The paper deals with studying a connection of the Littlewood--Offord problem with estimating the concentration functions of some symmetric infinitely divisible distributions. It is shown that the values at zero of the concentration…

Probability · Mathematics 2022-08-04 Andrei Yu. Zaitsev

The aim of this note is to investigate the Kolmogorov distance of the Circular Law to the empirical spectral distribution of non-Hermitian random matrices with independent entries. The optimal rate of convergence is determined by the…

Probability · Mathematics 2021-04-12 Friedrich Götze , Jonas Jalowy

We determine the distributional behavior for products of free random variables in a general infinitesimal triangular array. In the case of positive variables, the main theorem extends a result proved earlier for arrays with identically…

Operator Algebras · Mathematics 2007-05-23 Hari Bercovici , Jiun-Chau Wang

We show that external randomization may enforce the convergence of test statistics to their limiting distributions in particular cases. This results in a sharper inference. Our approach is based on a central limit theorem for weighted sums.…

Statistics Theory · Mathematics 2022-11-17 Nikita Puchkin , Vladimir Ulyanov

Consider the random polytope, that is given by the convex hull of a Poisson point process on a smooth convex body in $\mathbb{R}^d$. We prove central limit theorems for continuous motion invariant valuations including the Will's functional…

Probability · Mathematics 2019-04-02 Jens Grygierek

We analyzed the effect of the deviation of the exact distribution of the p-values from the uniform distribution on the Kolmogorov-Smirnov (K-S) test that was implemented as the second-level randomness test. We derived an inequality that…

Methodology · Statistics 2021-10-18 Akihiro Yamaguchi , Asaki Saito

If $f$ is a function of $n$ variables that is locally $L^1$ approximable by a sequence of smooth functions satisfying local $L^1$ bounds on the determinants of the minors of the Hessian, then $f$ admits a second order Taylor expansion…

Functional Analysis · Mathematics 2013-05-13 Joseph H. G. Fu