Density deconvolution with associated stationary data

Pub Date : 2023-09-03 DOI:10.21136/AM.2023.0135-22
Le Thi Hong Thuy, Cao Xuan Phuong
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Abstract

We study the density deconvolution problem when the random variables of interest are an associated strictly stationary sequence and the random noises are i.i.d. with a nonstandard density. Based on a nonparametric strategy, we introduce an estimator depending on two parameters. This estimator is shown to be consistent with respect to the mean integrated squared error. Under additional regularity assumptions on the target function as well as on the density of noises, some error estimates are derived. Several numerical simulations are also conducted to illustrate the efficiency of our method.

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与相关平稳数据的密度反褶积
研究了当随机变量为关联严格平稳序列且随机噪声为非标准密度时的密度反褶积问题。基于非参数策略,我们引入了一个依赖于两个参数的估计量。这个估计量与平均积分平方误差是一致的。在对目标函数和噪声密度附加的规则性假设下,得到了一些误差估计。数值模拟结果表明了该方法的有效性。
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