This paper proposes wavelet-M-estimation for time-varying coefficient time series models by using a robust-type wavelet technique, which can adapt to local features of the time-varying coefficients and does not require the smoothness of the unknown time-varying coefficient. The wavelet-M-estimation has the desired asymptotic properties and can be used to estimate conditional quantile and to robustify the usual mean regression. Under mild assumptions, the Bahadur representation and the asymptotic normality of wavelet-M-estimation are established.

中文翻译：

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时变系数时间序列模型的小波M估计

本文提出了一种鲁棒型小波技术，用于时变系数时间序列模型的小波M估计，该模型能够适应时变系数的局部特征，并且不需要平滑未知时变系数。小波M估计具有所需的渐近性质，可用于估计条件分位数并增强通常的均值回归。在温和的假设下，建立了Bahadur表示和小波M估计的渐近正态性。