We propose a monotone approximation scheme for two fully nonlinear PDEs. The first equation is Peng'sG-equation for characterizingG-distribution under sublinear expectation, and the second one is a fully nonlinear partial integro-differential equation for characterizing nonlinear alpha-stable distribution. We establish explicit error bounds for the approximation scheme by using and extending techniques introduced by Krylov and Barles-Jakobsen.  As an application, we obtain the convergence rate of Peng's robust central limit theorem and Bayraktar-Munk'a generalized central limit theorem for alpha-stable random variables under sublinear expectation. Based on joint work with Mingshang Hu, Shuo Huang and Lianzi Jiang. 

11.12海报.pdf