Central limit theorems for sub-linear expectation under the Lindeberg condition

DOI10.1186/s13660-018-1901-xzbMath1498.60091OpenAlexW2900627768WikidataQ59799114 ScholiaQ59799114MaRDI QIDQ824885

Cheng Hu

Publication date: 15 December 2021

Published in: Journal of Inequalities and Applications (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1186/s13660-018-1901-x

zbMATH Keywords

capacitycentral limit theoremLindeberg conditionsub-linear expectationG-normal distribution

Mathematics Subject Classification ID

Central limit and other weak theorems (60F05) Stochastic ordinary differential equations (aspects of stochastic analysis) (60H10) Strong limit theorems (60F15) Applications of stochastic analysis (to PDEs, etc.) (60H30) Stochastic integrals (60H05)

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Cites Work

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• Quasi-continuous random variables and processes under the \(G\)-expectation framework
• Rosenthal's inequalities for independent and negatively dependent random variables under sub-linear expectations with applications
• A strong law of large numbers for sub-linear expectation under a general moment condition
• Exponential inequalities under the sub-linear expectations with applications to laws of the iterated logarithm
• Central limit theorem for capacities
• Function spaces and capacity related to a sublinear expectation: application to \(G\)-Brownian motion paths
• A general central limit theorem under sublinear expectations
• Moment bounds for IID sequences under sublinear expectations
• Central limit theorem under variance uncertainty
• Survey on normal distributions, central limit theorem, Brownian motion and the related stochastic calculus under sublinear expectations
• Densities and summability
• A central limit theorem for \(m\)-dependent random variables under sublinear expectations
• Multi-dimensional central limit theorems and laws of large numbers under sublinear expectations
• A strong law of large numbers for non-additive probabilities
• Complete convergence and complete moment convergence for weighted sums of extended negatively dependent random variables under sub-linear expectation
• Theory of capacities
• Coherent Measures of Risk
• A Weighted Central Limit Theorem Under Sublinear Expectations
• The central limit theorem for summability methods of I.I.D. random variables
• ON STATISTICAL CONVERGENCE

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