arXiv subjects

Xiaohui Ma

Publications and source records attributed to Xiaohui Ma.

4 recordsLinked to original sources

arXiv2022

On Wasserstein-1 distance in the central limit theorem for elephant random walk

Recently, the elephant random walk has attracted a lot of attentions. A wide range of literature is available for the asymptotic behavior of the process, such as the central limit theorems, functional limit theorems and the law of iterated logarithm. However, there is not result concerning Wassertein-1 distance for the normal approximations.In this paper, we show that the Wassertein-1 distance in the central limit theorem is totally different when a memory parameter $p$ belongs to one of the three cases $0< p < 1/2,$ $1/2< p<3/4$ and $p=3/4.$

math.PR↗

arXiv2021

Cramér moderate deviations for the elephant random walk

We establish some limit theorems for one-dimensional elephant random walk, including Berry-Esseen bounds, Cramér moderate deviations and local limit theorems. These limit theorems can be regarded as refinements of the central limit theorems for the elephant random walk. Moreover, by these limit theorems, we conclude that the domain of attraction of normal distribution mainly depends on a memory parameter $p$ which lies between $0$ and $3/4.$

math.PR↗

arXiv2020

On the Wassertein distance for a martingale central limit theorem

We prove an upper bound on the Wassertein distance between normalized martingales and the standard normal random variable, which extends a result of Röllin [Statist. Probabil. Lett. 138 (2018) 171-176]. The proof is based on a method of Bolthausen [Ann. Probab. 10 (1982) 672-688].

math.PR↗

arXiv2020

A Berry-Esseen bound of order $ 1/\sqrt{n} $ for martingales

Renz (Ann. Probab. 1996) has established a rate of convergence $1/\sqrt{n}$ in the central limit theorem for martingales with some restrictive conditions. In the present paper a modification of the methods, developed by Bolthausen (Ann. Probab. 1982) and Grama and Haeusler (Stochastic Process. Appl. 2000), is applied for obtaining the same convergence rate for a class of more general martingales. An application to linear processes is discussed.

math.PR↗