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On Some Ambiguities Associated With The Fitting Of Arma Models To Time Series

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  • David F. Findley

Abstract

. Examples are presented illustrating some ambiguities associated with the application of ARMA models to problems of signal extraction, multistep‐ahead forecasting, spectrum approximation and linear quadratic control. Except in the signal extraction example, the ambiguities arise either from lack of sufficient autocovariance data to completely determine the process, or, often relatedly, from the approximate nature of the models used.

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  • David F. Findley, 1984. "On Some Ambiguities Associated With The Fitting Of Arma Models To Time Series," Journal of Time Series Analysis, Wiley Blackwell, vol. 5(4), pages 213-225, July.
    • Handle: RePEc:bla:jtsera:v:5:y:1984:i:4:p:213-225
    DOI: 10.1111/j.1467-9892.1984.tb00388.x
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    Cited by:

    1. Ismael Sanchez & Daniel Pena, 2001. "Properties of Predictors in Overdifferenced Nearly Nonstationary Autoregression," Journal of Time Series Analysis, Wiley Blackwell, vol. 22(1), pages 45-66, January.
    2. Panagiotis Mantalos & Kyriacos Mattheou & Alex Karagrigoriou, 2010. "Vector autoregressive order selection and forecasting via the modified divergence information criterion," International Journal of Computational Economics and Econometrics, Inderscience Enterprises Ltd, vol. 1(3/4), pages 254-277.

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