Stein's method for the law of large numbers under sublinear expectations
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Publication:2671643
DOI10.3934/puqr.2021010zbMath1497.60028arXiv1904.04674OpenAlexW3200653514MaRDI QIDQ2671643
Publication date: 3 June 2022
Published in: Probability, Uncertainty and Quantitative Risk (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/1904.04674
Central limit and other weak theorems (60F05) Sums of independent random variables; random walks (60G50)
Related Items (4)
Distributional Uncertainty of the Financial Time Series Measured by $G$-Expectation ⋮ Laws of large numbers under model uncertainty with an application to \(m\)-dependent random variables ⋮ A strong law of large numbers under sublinear expectations ⋮ \( G\)-expectation approach to stochastic ordering
Cites Work
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- Stein type characterization for \(G\)-normal distributions
- Function spaces and capacity related to a sublinear expectation: application to \(G\)-Brownian motion paths
- Law of large numbers and central limit theorem under nonlinear expectations
- On Shige Peng's central limit theorem
- Normal approximation by Stein's method under sublinear expectations
- Limit theorems with rate of convergence under sublinear expectations
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