Finite sample FPE and AIC criteria for autoregressive model order selection using same-realization predictions

DOI10.1155/2009/475147zbMath1192.94050OpenAlexW2091380732WikidataQ59250285 ScholiaQ59250285MaRDI QIDQ983765

Mahmood Karimi, Shapoor Khorshidi

Publication date: 26 July 2010

Published in: EURASIP Journal on Advances in Signal Processing (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1155/2009/475147

Mathematics Subject Classification ID

Signal theory (characterization, reconstruction, filtering, etc.) (94A12)

Related Items (1)

New autoregressive (AR) order selection criteria based on the prediction error estimation

Cites Work

• Order selection for same-realization predictions in autoregressive processes
• Statistical predictor identification
• Accumulated prediction errors, information criteria and optimal forecasting for autoregressive time series
• Autoregressive model order selection by a finite sample estimator for the Kullback-Leibler discrepancy
• Order selection for AR models by predictive least squares
• A Small Sample Model Selection Criterion Based on Kullback's Symmetric Divergence
• On the residual variance and the prediction error for the LSF estimation method and new modified finite sample criteria for autoregressive model order selection

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