L1 common trend filtering: an extension
L1 common trend filtering: an extension
复制标题
L1 共同趋势过滤：扩展
DOI：
10.1080/00949655.2022.2144314
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发表时间：
2022
影响因子：
1.2
通讯作者：
Hayakawa Kazuhiko
中科院分区：
文献类型：
--
作者：
Bao Ruoyi;Yamada Hiroshi;Hayakawa Kazuhiko
共同趋势滤波使我们能够同时估计多个时间序列的共同连续分段线性趋势和相应的因子负荷系数。在本文中，我们扩展这一替代识别限制识别限制，并开发一个算法来解决这个新问题。由于新的辨识约束是线性的，它可以包含其它参数的线性约束。使用这种修改，例如，我们可以估计因子加载系数的向量，使得其两个条目相等，这是当前共同趋势滤波无法处理的。我们还提供了一种方法来指定新问题的调整参数，并以经验说明算法的工作原理。
common trend filtering enables us to estimate a common continuous piecewise linear trend and the corresponding factor loading coefficients of multiple time series simultaneously. In this paper, we extend this by replacing the identifying restriction with an alternative identifying restriction and develop an algorithm for solving this new problem. As the new identifying restriction is linear, it can include other linear restrictions of parameters. Using this modification, e.g. we can estimate the vector of the factor loading coefficients so that its two entries will equal, which currentcommon trend filtering cannot handle. We also provide a way of specifying the tuning parameter of the new problem and empirically illustrate how well the algorithm works.