Time-Series Main Trend Analysis by Adaptive Dynamics Model
Xuebo Jin, Nian-Xiang Yang, Tingli Su, Jianlei Kong · 2018
For high-frequency fluctuations of time-series data, it is necessary to extract and analyze the main trend for many applications. This paper focuses on the main trend analysis by Kalman filter, gives the extraction model and the transform model, and discusses the suitable value for the key parameters to guarantee the system convergence. The high order dimensional dynamics of the main trend are analyzed by the estimate results. The simulations show that the developed method is effective for extracting the main trend of the time-series data and able to explain accurately the characteristics of the main trend.