A central limit theorem under sublinear expectations

Abstract

In this paper we consider a sequence of random variables with mean uncertainty in a sublinear expectation space. Without the hypothesis of identical distributions, we show a new central limit theorem under the sublinear expectations.

References in corpus (3)

• A New Central Limit Theorem under Sublinear Expectations
• G-Brownian Motion and Dynamic Risk Measure under Volatility Uncertainty
• Law of Large Numbers and Central Limit Theorem under Nonlinear Expectations

Cited by in corpus (7)

• The convergence of the sums of independent random variables under the sub-linear expectations
• Lindeberg's central limit theorems for martingale like sequences under sub-linear expectations
• An $\alpha$-stable limit theorem under sublinear expectation
• A monotone scheme for G-equations with application to the explicit convergence rate of robust central limit theorem
• General laws of large numbers under sublinear expectations
• A weighted central limit theorem under sublinear expectations
• Multi-dimensional central limit theorems and laws of large numbers under sublinear expectations