Title :
Time series analysis and its application
Author_Institution :
Dept. Of Math., China Univ. Of Min.&Technol., Beijing
Abstract :
This paper studies the smoothness of time series with trends, seasonality and stationary term. The equality of constraint smoothing estimate, priors-Bayes smoothing estimate and some type of Kalman smoothing estimate is proved theoretically. And the state space expression described by prior-Bayes is obtained for the smoothness of time series. Itpsilas the theoretical base for using Kalman filter algorithm and estimating order and parameters of constraint smoothing.
Keywords :
Bayes methods; Kalman filters; estimation theory; smoothing methods; time series; Kalman filter algorithm; Kalman smoothing estimate; constraint smoothing estimate; estimating order; priors-Bayes smoothing estimate; seasonality; stationary term; time series analysis; time series smoothness; Constraint theory; Electronic mail; Estimation theory; Kalman filters; Mathematics; Smoothing methods; Space technology; State estimation; State-space methods; Time series analysis; Bayes smoothing estimation; Kalman filter; state pace model;
Conference_Titel :
Control and Decision Conference, 2008. CCDC 2008. Chinese
Conference_Location :
Yantai, Shandong
Print_ISBN :
978-1-4244-1733-9
Electronic_ISBN :
978-1-4244-1734-6
DOI :
10.1109/CCDC.2008.4598191
