Common seasonality in multivariate time series
Common seasonality in multivariate time series
复制标题
多元时间序列中的常见季节性
DOI：
10.5705/ss.2014.184t
复制
发表时间：
2016
影响因子：
1.4
通讯作者：
Dagoberto Saboy´a
中科院分区：
文献类型：
--
作者：
Fabio H. Nieto;Daniel Pe˜na;Dagoberto Saboy´a
季节性多元时间序列的公因子通常通过对序列进行滤波以去除季节性成分，然后提取非季节性公因子来获得。这种方法有两个缺点。首先，我们无法检测具有季节性结构的共同因素;其次，众所周知，去季节化的时间序列可能会显示原始数据不包含的虚假周期，这可能会使检测季节性结构变得更加困难。fhnietos@unal.edu.co
Common factors for seasonal multivariate time series are usually obtained by first filtering the series to eliminate the seasonal component and then extracting the nonseasonal common factors. This approach has two drawbacks. First, we cannot detect common factors with seasonal structure; second, it is well known that a deseasonalized time series may exhibit spurious cycles that the original data do not contain, which can make more difficult the detection of ∗Corresponding author: fhnietos@unal.edu.co Phone (+57) 1-3165000