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

DOI10.1016/j.sigpro.2011.04.021zbMath1219.94034OpenAlexW1964994427MaRDI QIDQ635064

Juan-Miguel Gracia

Publication date: 19 August 2011

Published in: Signal Processing (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.sigpro.2011.04.021

zbMATH Keywords

prediction errorautoregressive model order selectionleast-squares-forward method

Mathematics Subject Classification ID

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

Related Items (2)

Sensing fractional power spectrum of nonstationary signals with coprime filter banks ⋮ Autoregressive models with mixture of scale mixtures of Gaussian innovations

Cites Work

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• Effects of not Knowing the Order of an Autoregressive Process on the Mean Squared Error of Prediction-1
• On Finite Sample Theory for Autoregressive Model Order Selection
• 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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