A comparison theorem under sublinear expectations and related limit theorems
Probability
2017-10-05 v1
Abstract
In this paper, on the sublinear expectation space, we establish a comparison theorem between independent and convolutionary random vectors, which states that the partial sums of those two sequences of random vectors are identically distributed. Under the sublinear framework, through the comparison theorem, several fundamental limit theorems for convolutionary random vectors are obtained, including the law of large numbers, the central limit theorem and the law of iterated logarithm.
Cite
@article{arxiv.1710.01624,
title = {A comparison theorem under sublinear expectations and related limit theorems},
author = {Ning Zhang and Yuting Lan},
journal= {arXiv preprint arXiv:1710.01624},
year = {2017}
}