The paper deals with designing a mask suitable for a selective filtering of data. The design of the mask is performed in the time-frequency domain and the selection is based on the co-movement measure of time series. We propose two approaches for the mask construction: i) hard thresholding based on ${\chi }^2$ testing; ii) adaptive based thresholding. The proposed mask can be used for time series filtering in which we obtain either the adjusted time series or the construction of the time series containing only the co-moved parts. Further, after computing an inverse transform we can obtain time series with/without the co-moved area applicable for consequent econometric analyses. The paper provides recommendations concerning the selection of a particular approach in a given situation. The proposed methodology is demonstrated on the adjustment of industrial production index of Euro Area and selected G8 countries about co-movement with the US.

本文涉及设计适用于选择性过滤数据的掩模。掩模的设计在时频域中进行，并且选择基于时间序列的共同运动度量。我们提出了两种掩模构造方法：i）基于阈值的硬阈值${\chi }^{\mathrm{2个}}$测试；ii）基于自适应的阈值。提议的遮罩可用于时间序列过滤，在其中我们可以获取调整后的时间序列或仅包含共同移动部分的时间序列的构造。此外，在计算了逆变换之后，我们可以获得带/不带共同移动区域的时间序列，可用于随后的计量经济分析。本文提供了有关在给定情况下选择特定方法的建议。在调整欧元区和选定的八国集团与美国合作方面的国家的工业生产指数时，论证了所建议的方法。