DocumentCode :
3223990
Title :
Modified AIC and FPE criteria for autoregressive (AR) model order selection by using LSFB estimation method
Author :
Khorshidi, Sh ; Karimi, M.
fYear :
2009
fDate :
15-17 July 2009
Firstpage :
374
Lastpage :
379
Abstract :
The Least-Squares-Forward-Backward (LSFB) method for estimating the parameters of the autoregressive (AR) model is considered and new theoretical approximations for expectations of the prediction error and the residual variance are derived. These results are used for modifying the AR order selection criteria FPE and AIC. The performance of these modified criteria is compared with other AR order selection criteria using simulated data. The results of these performance comparisons show that the new criteria have better performance in the finite sample case.
Keywords :
autoregressive processes; least squares approximations; parameter estimation; autoregressive model order selection; least squares forward-backward estimation; parameter estimation; Parameter estimation; Pattern classification; Power capacitors; Predictive models; Radar applications; Radar signal processing; Signal detection; Sonar; Speech processing; System identification;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Advances in Computational Tools for Engineering Applications, 2009. ACTEA '09. International Conference on
Conference_Location :
Zouk Mosbeh
Print_ISBN :
978-1-4244-3833-4
Electronic_ISBN :
978-1-4244-3834-1
Type :
conf
DOI :
10.1109/ACTEA.2009.5227941
Filename :
5227941
Link To Document :
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