On complete convergence for extended independent random variables under sub-linear expectations
From MaRDI portal
Publication:5108981
DOI10.4134/JKMS.j190093zbMath1434.60101OpenAlexW3033196033MaRDI QIDQ5108981
Publication date: 7 May 2020
Full work available at URL: https://www.koreascience.or.kr:443/article/JAKO202012941167317.pdf
Related Items
Complete convergence for weighted sums of widely orthant-dependent random variables and its statistical application, Complete convergence for END random variables under sublinear expectations
Cites Work
- Unnamed Item
- 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
- Central limit theorem for capacities
- On Cramér's theorem for capacities
- A theoretical framework for the pricing of contingent claims in the presence of model uncertainty
- Survey on normal distributions, central limit theorem, Brownian motion and the related stochastic calculus under sublinear expectations
- Expected utility with purely subjective non-additive probabilities
- Limit laws for non-additive probabilities and their frequentist interpretation
- On the strong law for arrays and for the bootstrap mean and variance
- Strong law of large numbers and Chover's law of the iterated logarithm under sub-linear expectations
- Law of large numbers and central limit theorem under nonlinear expectations
- Complete convergence for arrays of rowwise END random variables and its statistical applications under sub-linear expectations
- A strong law of large numbers for non-additive probabilities
- On the asymptotic approximation of inverse moment under sub-linear expectations
- Multi-dimensional \(G\)-Brownian motion and related stochastic calculus under \(G\)-expectation
- Minimax tests and the Neyman-Pearson lemma for capacities
- Ambiguity, Risk, and Asset Returns in Continuous Time
- Convergence Rates in the Law of Large Numbers
- Complete Convergence and the Law of Large Numbers
