Theorems of complete convergence and complete integral convergence for END random variables under sub-linear expectations
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Publication:2067842
DOI10.1186/S13660-019-2064-0zbMath1499.60088OpenAlexW2947087966WikidataQ127963646 ScholiaQ127963646MaRDI QIDQ2067842
Publication date: 19 January 2022
Published in: Journal of Inequalities and Applications (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1186/s13660-019-2064-0
Central limit and other weak theorems (60F05) Sums of independent random variables; random walks (60G50) Strong limit theorems (60F15) (L^p)-limit theorems (60F25)
Related Items (4)
Complete consistency for the weighted least squares estimators in semiparametric regression models ⋮ Complete convergence theorems for arrays of row-wise extended negatively dependent random variables under sub-linear expectations ⋮ Complete convergence for weighted sums of widely orthant-dependent random variables and its statistical application ⋮ Complete convergence for weighted sums of widely acceptable random variables under sublinear expectations
Cites Work
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- 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
- Complete convergence and complete moment convergence for negatively associated sequences of random variables
- Exponential inequalities under the sub-linear expectations with applications to laws of the iterated logarithm
- A general central limit theorem under sublinear expectations
- An intermediate Baum-Katz theorem
- Precise large deviations for dependent random variables with heavy tails
- Cesàro \({\alpha}\)-integrability and laws of large numbers. I
- Marcinkiewicz's strong law of large numbers for nonlinear expectations
- Strong law of large numbers and Chover's law of the iterated logarithm under sub-linear expectations
- Three series theorem for independent random variables under sub-linear expectations with applications
- Complete moment convergence for i.i.d. random variables
- Multi-dimensional \(G\)-Brownian motion and related stochastic calculus under \(G\)-expectation
- The Strong Law of Large Numbers for Extended Negatively Dependent Random Variables
- CONVERGENCE PROPERTIES OF THE PARTIAL SUMS FOR SEQUENCES OF END RANDOM VARIABLES
- Complete convergence for weighted sums of negatively dependent random variables under the sub-linear expectations
- Limiting behaviour for arrays of row-wise END random variables under conditions of h-integrability
- WEAK LAWS OF LARGE NUMBERS FOR ARRAYS UNDER A CONDITION OF UNIFORM INTEGRABILITY
- Complete Convergence and the Law of Large Numbers
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