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- W2077165791 abstract "The well-known prediction-error-based maximum likelihood (PEML) method can only handle minimum phase ARMA models. This paper presents a new method known as the back-filtering-based maximum likelihood (BFML) method, which can handle nonminimum phase and noncausal ARMA models. The BFML method is identical to the PEML method in the case of a minimum phase ARMA model, and it turns out that the BFML method incorporates a noncausal ARMA filter with poles outside the unit circle for estimation of the parameters of a causal, nonminimum phase ARMA model.< <ETX xmlns:mml=http://www.w3.org/1998/Math/MathML xmlns:xlink=http://www.w3.org/1999/xlink>></ETX>" @default.
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- W2077165791 date "1994-01-01" @default.
- W2077165791 modified "2023-09-27" @default.
- W2077165791 title "Maximum likelihood estimation of the parameters of nonminimum phase and noncausal ARMA models" @default.
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- W2077165791 doi "https://doi.org/10.1109/78.258141" @default.
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