Convergence for sums of i.i.d. random variables under sublinear expectations
DOI10.1186/s13660-021-02692-xzbMath1504.60052arXiv2104.10430OpenAlexW3199473849MaRDI QIDQ2072954
Publication date: 26 January 2022
Published in: Journal of Inequalities and Applications (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/2104.10430
capacityweighted sumsindependent identically distributed random variablescomplete moment convergencesublinear expectation
Central limit and other weak theorems (60F05) Stochastic ordinary differential equations (aspects of stochastic analysis) (60H10) Strong limit theorems (60F15) Generalizations of martingales (60G48) Functional limit theorems; invariance principles (60F17)
Related Items (2)
Cites Work
- Unnamed Item
- Unnamed Item
- Rosenthal's inequalities for independent and negatively dependent random variables under sub-linear expectations with applications
- Strong laws of large numbers for sub-linear expectations
- How big are the increments of \(G\)-Brownian motion?
- Exponential inequalities under the sub-linear expectations with applications to laws of the iterated logarithm
- Some inequalities and limit theorems under sublinear expectations
- Strong laws of large numbers for general random variables in sublinear expectation spaces
- Donsker's invariance principle under the sub-linear expectation with an application to Chung's law of the iterated logarithm
- Complete convergence and complete moment convergence for weighted sums of extended negatively dependent random variables under sub-linear expectation
- Strong convergence for sequences of asymptotically almost negatively associated random variables
- Large deviations and moderate deviations for independent random variables under sublinear expectations
This page was built for publication: Convergence for sums of i.i.d. random variables under sublinear expectations
