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We describe a new framework of a sublinear expectation space and the related notions and results of distributions, independence. A new notion of G-distributions is introduced which generalizes our G-normal-distribution in the sense that…

Probability · Mathematics 2008-03-19 Shige Peng

In this paper, we investigate a central limit theorem for weighted sums of independent random variables under sublinear expectations. It is turned out that our results are natural extensions of the results obtained by Peng and Li and Shi.

Probability · Mathematics 2011-05-05 Defei Zhang

In this paper, we obtain a new estimate for uniform integrability under sublinear expectations. Based on this, we establish the limit theorems under nonlinear expectations dominated by sublinear expectations through tightness, and the limit…

Probability · Mathematics 2025-06-23 Xiaojuan Li , Mingshang Hu

In this paper, we present some multi-dimensional central limit theorems and laws of large numbers under sublinear expectations, which extend some previous results.

Probability · Mathematics 2013-06-20 Ze-Chun Hu , Ling Zhou

Under the sublinear expectation $\mathbb{E}[\cdot]:=\sup_{\theta\in \Theta} E_\theta[\cdot]$ for a given set of linear expectations $\{E_\theta: \theta\in \Theta\}$, we establish a new law of large numbers and a new central limit theorem…

Probability · Mathematics 2018-05-16 Xiao Fang , Shige Peng , Qi-Man Shao , Yongsheng Song

We prove a central limit theorem for a sequence of random variables whose means are ambiguous and vary in an unstructured way. Their joint distribution is described by a set of measures. The limit is (not the normal distribution and is)…

Probability · Mathematics 2020-07-01 Zengjing Chen , Larry G. Epstein

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 introduce a new basic model for independent and identical distributed sequence on the canonical space $(\mathbb{R}^\mathbb{N},\mathcal{B}(\mathbb{R}^\mathbb{N}))$ via probability kernels with model uncertainty. Thanks to the well-defined…

Probability · Mathematics 2022-03-02 Xinpeng Li

In this paper, by using the representation theorem for sublinear expectations, we give a simple proof to obtain two inequalities about the sample mean for independent random vectors under sublinear expectations.

Probability · Mathematics 2024-10-16 Xiaojuan Li , Mingshang Hu

In this paper, on the sublinear expectation space, we establish a comparison theorem between independent and convolutionary random vectors, which states that the partial sums of those two sequences of random vectors are identically…

Probability · Mathematics 2017-10-05 Ning Zhang , Yuting Lan

For $\alpha\in (1,2)$, we present a generalized central limit theorem for $\alpha$-stable random variables under sublinear expectation. The foundation of our proof is an interior regularity estimate for partial integro-differential…

Probability · Mathematics 2016-06-28 Erhan Bayraktar , Alexander Munk

A central limit theorem is established for a sum of random variables belonging to a sequence of random fields. The fields are assumed to have zero mean conditional on the past history and to satisfy certain conditional $\alpha$-mixing…

Probability · Mathematics 2024-09-17 Abdollah Jalilian , Arnaud Poinas , Ganggang Xu , Rasmus Waagepetersen

Nonlinear expectation, including sublinear expectation as its special case, is a new and original framework of probability theory and has potential applications in some scientific fields, especially in finance risk measure and management.…

Statistics Theory · Mathematics 2013-04-15 Lu Lin , Yufeng Shi , Xin Wang , Shuzhen Yang

Peng (2006) initiated a new kind of central limit theorem under sub-linear expectations. Song (2017) gave an estimate of the rate of convergence of Peng's central limit theorem. Based on these results, we establish a new kind of almost sure…

Probability · Mathematics 2018-10-19 Weihuan Huang , Panyu Wu

In this book, we introduce a new approach of sublinear expectation to deal with the problem of probability and distribution model uncertainty. We a new type of (robust) normal distributions and the related central limit theorem under…

Probability · Mathematics 2010-02-25 Shige Peng

M-dependence is a commonly used assumption in the study of dependent sequences. In this paper, central limit theorems for m-dependent random variables under the sub-linear expectations are established based mainly on the conditions of…

Probability · Mathematics 2023-09-12 Wang-Yun Gu , Li-Xin Zhang

A non-classical formulation of the central limit theorem is given for sequences of independent random variables with finite second moments. Singular sequences whose members all have a degenerate or normal distribution are excluded from…

Probability · Mathematics 2025-01-29 Alexander Shmyrov , Vasily Shmyrov

A central limit theorem for arrays of symmetric row-wise exchangeable random variables is presented. The result is valid for finite and infinite extendable and non-extendable sequences. Unlike most reported versions of the central limit…

Probability · Mathematics 2020-06-22 Ilya Soloveychik

In this paper, with the notion of independent identically distributed (IID) random variables under sublinear expectations introduced by Peng [7-9], we investigate moment bounds for IID sequences under sublinear expectations. We can obtain a…

Probability · Mathematics 2015-05-28 Feng Hu

We study central limit theorems for certain nonlinear sequences of random variables. In particular, we prove the central limit theorems for the bounded conductivity of the random resistor networks on hierarchical lattices.

Disordered Systems and Neural Networks · Physics 2007-05-23 Jung M. Woo , Jan Wehr
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