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Some Properties Of Autoregressive Estimates For Processes With Mixed Spectra

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  • M. S. Mackisack
  • D. S. Poskitt

Abstract

. A formal justification for the use of the method of autoregressive spectral estimation for time series consisting of a sinusoidal signal in additive noise is given in this paper. The analytical properties of the autoregressive approximation to the generalized spectral density of the process are presented, and the operational characteristics of the statistical estimation procedure are discussed. In particular, strong convergence of the autoregressive parameters and the autoregressive transfer function approximation is shown.

Suggested Citation

  • M. S. Mackisack & D. S. Poskitt, 1990. "Some Properties Of Autoregressive Estimates For Processes With Mixed Spectra," Journal of Time Series Analysis, Wiley Blackwell, vol. 11(4), pages 325-337, July.
    • Handle: RePEc:bla:jtsera:v:11:y:1990:i:4:p:325-337
    DOI: 10.1111/j.1467-9892.1990.tb00061.x
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    Cited by:

    1. Charles Kooperberg & Charles J. Stone & Young K. Truong, 1995. "Logspline Estimation Of A Possibly Mixed Spectral Distribution," Journal of Time Series Analysis, Wiley Blackwell, vol. 16(4), pages 359-388, July.
    2. Chen, Bei & Gel, Yulia R., 2010. "Autoregressive frequency detection using Regularized Least Squares," Journal of Multivariate Analysis, Elsevier, vol. 101(7), pages 1712-1727, August.

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