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20102023
most citedCramér Type Moderate Deviations for Random Fields

13 citations · 38 across the 26 of their papers we have counts for

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7 papers · 1 filter

math.PR2021

Limit theorems for linear random fields with innovations in the domain of attraction of a stable law

Magda Peligrad, Hailin Sang, Yimin Xiao +1

In this paper we study the convergence in distribution and the local limit theorem for the partial sums of linear random fields with i.i.d. innovations that have infinite second mo…

math.PR2020★ 1 cited

A Local Limit Theorem for Linear Random Fields

Timothy Fortune, Magda Peligrad, Hailin Sang

In this paper, we establish a local limit theorem for linear fields of random variables constructed from independent and identically distributed innovations each with finite second…

math.PR2020

A Berry-Esseen bound of order for martingales

Songqi Wu, Xiaohui Ma, Hailin Sang +1

Renz (Ann. Probab. 1996) has established a rate of convergence in the central limit theorem for martingales with some restrictive conditions. In the present paper a mo…

math.PR2017★ 6 cited

Exact Moderate and Large Deviations for Linear Random Fields

Hailin Sang, Yimin Xiao

By extending the methods in Peligrad et al. (2014a, b), we establish exact moderate and large deviation asymptotics for linear random fields with independent innovations. These res…

math.PR2015★ 1 cited

On kernel estimators of density for reversible Markov chains

Martial Longla, Magda Peligrad, Hailin Sang

In this paper we investigate the kernel estimator of the density for a stationary reversible Markov chain. The proofs are based on a new central limit theorem for a triangular arra…

math.PR2013

Further Refinement of Self-normalized Cram\a'{e}r-type moderate Deviations

Hailin Sang, Lin Ge

In this paper, we study the self-normalized Cram\a'{e}r-type moderate deviations for centered independent random variables with . The main resul…

math.PR2011

Central Limit Theorem for Linear Processes with Infinite Variance

Magda Peligrad, Hailin Sang

This paper addresses the following classical question: giving a sequence of identically distributed random variables in the domain of attraction of a normal law, does the associate…