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20112022
most citedCramér Type Moderate Deviations for Random Fields

13 citations · 17 across the 12 of their papers we have counts for

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math.ST2022

On the integrated mean squared error of wavelet density estimation for linear processes

Aleksandr Beknazaryan, Hailin Sang, Peter Adamic

Let be a linear process with density function . We study wavelet density estimation of . Under some regular conditions on the characterist…

math.ST2021

Variable bandwidth kernel regression estimation

Janet Nakarmi, Hailin Sang, Lin Ge

In this paper we propose a variable bandwidth kernel regression estimator for observations in to improve the classical Nadaraya-Watson estimator. The bias i…

math.ST2020

Shannon entropy estimation for linear processes

Timothy Fortune, Hailin Sang

In this paper, we estimate the Shannon entropy $S(f) = -\E[ \log (f(x))]$ of a one-sided linear process with probability density function . We employ the integral estimator $…

math.ST201913 cited

Cramér Type Moderate Deviations for Random Fields

Aleksandr Beknazaryan, Hailin Sang, Yimin Xiao

We study the Cramér type moderate deviation for partial sums of random fields by applying the conjugate method. The results are applicable to the partial sums of linear random fiel…

math.ST20181 cited

On mutual information estimation for mixed-pair random variables

Aleksandr Beknazaryan, Xin Dang, Hailin Sang

We study the mutual information estimation for mixed-pair random variables. One random variable is discrete and the other one is continuous. We develop a kernel method to estimate…

math.ST2017

Central limit theorem for the variable bandwidth kernel density estimators

Janet Nakarmi, Hailin Sang

In this paper we study the ideal variable bandwidth kernel density estimator introduced by McKay (1993) and Jones, McKay and Hu (1994) and the plug-in practical version of the vari…