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We obtain the best possible upper bounds for the moments of a single order statistic from independent, non-negative random variables, in terms of the population mean. The main result covers the independent identically distributed case.…

Statistics Theory · Mathematics 2018-06-14 Nickos Papadatos

We define the local empirical process, based on $n$ i.i.d. random vectors in dimension $d$, in the neighborhood of the boundary of a fixed set. Under natural conditions on the shrinking neighborhood, we show that, for these local empirical…

Statistics Theory · Mathematics 2011-04-22 John H. J. Einmahl , Estáte V. Khmaladze

We develop novel empirical Bernstein inequalities for the variance of bounded random variables. Our inequalities hold under constant conditional variance and mean, without further assumptions like independence or identical distribution of…

Statistics Theory · Mathematics 2026-05-28 Diego Martinez-Taboada , Aaditya Ramdas

A prophet inequality states, for some $\alpha\in[0,1]$, that the expected value achievable by a gambler who sequentially observes random variables $X_1,\dots,X_n$ and selects one of them is at least an $\alpha$ fraction of the maximum value…

Data Structures and Algorithms · Computer Science 2020-11-24 José Correa , Paul Dütting , Felix Fischer , Kevin Schewior , Bruno Ziliotto

In this paper, we introduce a fundamental model for independent and identically distributed sequence with model uncertainty on the canonical space $(\mathbb{R}^\mathbb{N},\mathcal{B}(\mathbb{R}^\mathbb{N}))$ via probability kernels. Thanks…

Probability · Mathematics 2023-07-25 Xiaofan Guo , Xinpeng Li

We study approximation of non-autonomous linear differential equations with variable delay over infinite intervals. We use piecewise constant argument to obtain a corresponding discrete difference equation. The study of numerical…

Classical Analysis and ODEs · Mathematics 2016-07-26 Daniel Sepúlveda

A notion of conditionally identically distributed (c.i.d.) sequences has been studied as a form of stochastic dependence that is weaker than exchangeability, but is equivalent to exchangeability for stationary sequences. In this article we…

Probability · Mathematics 2017-03-07 Sandra Fortini , Sonia Petrone , Polina Sporysheva

We study Edgeworth expansions in limit theorems for self-normalized sums. Non-uniform bounds for expansions in the central limit theorem are established while only imposing minimal moment conditions. Within this result, we address the case…

Probability · Mathematics 2022-08-11 Pascal Beckedorf , Angelika Rohde

Estimation of the complete distribution of a random variable is a useful primitive for both manual and automated decision making. This problem has received extensive attention in the i.i.d. setting, but the arbitrary data dependent setting…

Machine Learning · Statistics 2023-03-01 Paul Mineiro , Steven R. Howard

We consider the well-known problem of the computation of the (limiting) time-dependent performance characteristics of one-dimensional continuous-time birth and death processes on $\mathbb{Z}$ with time varying and possible state-dependent…

Probability · Mathematics 2021-10-18 Yacov Satin , Rostislav Razumchik , Alexander Zeifman , Ivan Kovalev

We establish bounds for the covariance of a large class of functions of infinite variance stable random variables, including unbounded functions such as the power function and the logarithm. These bounds involve measures of dependence…

Statistics Theory · Mathematics 2011-11-10 Vladas Pipiras , Murad S. Taqqu , Patrice Abry

In this paper, under some weaker conditions, we give three laws of large numbers under sublinear expectations (capacities), which extend Peng's law of large numbers under sublinear expectations in [8] and Chen's strong law of large numbers…

Probability · Mathematics 2012-02-10 Feng Hu

This paper addresses the following classical question: giving a sequence of identically distributed random variables in the domain of attraction of a normal law, does the associated linear process satisfy the central limit theorem? We study…

Probability · Mathematics 2011-06-01 Magda Peligrad , Hailin Sang

We construct a time-consistent sublinear expectation in the setting of volatility uncertainty. This mapping extends Peng's G-expectation by allowing the range of the volatility uncertainty to be stochastic. Our construction is purely…

Probability · Mathematics 2013-09-06 Marcel Nutz

In this paper, we consider the sublinear expectation on bounded random variables. With the notion of uncorrelatedness for random variables under the sublinear expectation, a weak law of large numbers is obtained. With the notion of…

Probability · Mathematics 2023-11-17 Wenhao Li , Chuanfeng Sun

Suppose that i.i.d. random variables $X_{1}, X_{2}, \ldots$ are chosen uniformly from $[0,1]$, and let $f: [0,1] \rightarrow [0,1]$ be an increasing bijection. Define $\mu_{f}$ to be the expected value of $f(X_{i})$ for each $i$. Define the…

Probability · Mathematics 2016-08-23 Jesse Geneson

In this paper, we prove a conditional limit theorem for independent not necessarily identically distributed random variables. Namely, we obtain the asymptotic distribution of a large number of them given the sum.

Statistics Theory · Mathematics 2020-11-12 Dimbihery Rabenoro

We prove some inequalities involving fourth central moment of a random variable that takes values in a given finite interval. Both discrete and continuous cases are considered. Bounds for the spread are obtained when a given nxn complex…

Statistics Theory · Mathematics 2015-03-13 R. Sharma , R. Kumar , R. Saini , G. Kapoor

This article relaxes the integrability condition imposed in the literature for the robust $\alpha$-stable central limit theorem under sublinear expectation. Specifically, for $\alpha \in(0,1]$, we prove that the normalized sums of i.i.d.…

Probability · Mathematics 2023-01-20 Lianzi Jiang , Gechun Liang

A famous result in renewal theory is the Central Limit Theorem for renewal processes. As in applications usually only observations from a finite time interval are available, a bound on the Kolmogorov distance to the normal distribution is…

Probability · Mathematics 2018-07-24 Gesine Reinert , Ce Yang