In this paper we propose a shrinkage wavelet-based method to estimate the signal in a nonparametric regression model with Autoregressive Fractionally Integrated Moving Average (ARFIMA) errors. Monte Carlo experiments indicate that the proposed method is better than the universal thresholding rule which is widely used in data analysis via wavelet regression models.

翻译：本文提出了一种基于小波收缩的方法，用于估计具有自回归分数阶积分移动平均（ARFIMA）误差的非参数回归模型中的信号。蒙特卡洛实验表明，该方法优于在小波回归模型数据分析中广泛使用的通用阈值规则。