Title :
A new order estimation technique for time series modeling
Author :
Davis, Mark H A ; Zheng, Wei Xing
Author_Institution :
Dept. of Electr. & Electron. Eng., Imperial Coll. of Sci., Technol. & Med., London, UK
fDate :
3/1/1997 12:00:00 AM
Abstract :
A new approach to estimating the order of the autoregressive moving average model is proposed, which is based on the approximate stochastic realization introduced in Davis and Fotopoulos (1991). The present approach is attractive because overparameterization-a very common problem in order determination-is avoided successfully. Simulation results are included to illustrate the effectiveness of the proposed order estimation approach
Keywords :
autoregressive moving average processes; modelling; parameter estimation; realisation theory; time series; approximate stochastic realization; autoregressive moving average model; order estimation technique; time series modeling; Autoregressive processes; Councils; Linear approximation; Probability; Signal processing; Signal processing algorithms; Stochastic processes; Stochastic resonance; System identification; White noise;
Journal_Title :
Automatic Control, IEEE Transactions on
