| Autor: |
Khorshidi, Sh., Towhidi, M., Karimi, M., Babazadeh, F. |
| Předmět: |
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| Zdroj: |
International Review of Automatic Control; Nov2009, Vol. 2 Issue 6, p614-620, 7p, 6 Charts |
| Abstrakt: |
One of the important problems in AR model estimation is the model order selection problem. There are many model order selection criteria that have been applied to the AR order selection problem. Some of these criteria such as FPE, FSC, MFSC, and FPEF are typically based on minimizing the prediction error, but these criteria are not actually optimal in the sense of prediction error. Here, we will provide conditions under which optimal predictive order selection criterion for AR model will be achieved. Then, we will apply this criterion to simulated data and compare its performance with that of other AR order selection criteria. Simulation results show that the new criterion has lower prediction error than the other AR order selection criteria. [ABSTRACT FROM AUTHOR] |
| Databáze: |
Complementary Index |
| Externí odkaz: |
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