We investigate an auto-regressive formulation for the problem of smoothing time-series by manipulating the inherent objective function of the traditional moving mean smoothers. Not only the auto-regressive smoothers enforce a higher degree of smoothing, they are just as efficient as the traditional moving means and can be optimized accordingly with respect to the input dataset. Interestingly, the auto-regressive models result in moving means with exponentially tapered windows.
翻译:我们通过操纵传统移动式平均平滑器的固有客观功能,对平滑时间序列问题的自动递减提法进行了调查。 不仅自动递减式平滑器能实施更高程度的平滑,而且与传统移动手段一样高效,在输入数据集方面可以相应地优化。 有趣的是,自动递减式模型可以导致以指数式压碎窗口进行移动。