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Linear Interpolators And The Inverse Correlation Function Of Non‐Stationary Time Series

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  • Roberto Baragona
  • Francesco Battaglia

Abstract

. The inverse correlation function of a stationary time series was introduced by Cleveland (The inverse autocorrelations of a time series and their applications. Technometrics 14 (1972), 277–93). In this paper inverse correlations are defined for non‐stationary time series {xt, integer t} such that yt= (1 —Bs)dxt is second‐order stationary. The linear interpolator and the inverse process of {xt} are also defined:their weights are shown to be time invariant and proportional to the inverse correlations. The interpolation method for the estimation of the inverse correlation function of a stationary time series is extended to the non‐stationary series {xt} and the asymptotic properties of the estimates are found to be similar to those in the stationary case.

Suggested Citation

  • Roberto Baragona & Francesco Battaglia, 1995. "Linear Interpolators And The Inverse Correlation Function Of Non‐Stationary Time Series," Journal of Time Series Analysis, Wiley Blackwell, vol. 16(6), pages 531-538, November.
    • Handle: RePEc:bla:jtsera:v:16:y:1995:i:6:p:531-538
    DOI: 10.1111/j.1467-9892.1995.tb00252.x
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    References listed on IDEAS

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    1. R. J. Bhansali, 1983. "A Simulation Study of Autoregressive and Window Estimators of the Inverse Correlation Function," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 32(2), pages 141-149, June.
    2. Francesco Battaglia, 1983. "Inverse Autocovariances And A Measure Of Linear Determinism For A Stationary Process," Journal of Time Series Analysis, Wiley Blackwell, vol. 4(2), pages 79-87, March.
    3. Francesco Battaglia, 1988. "On The Estimation Of The Inverse Correlation Function," Journal of Time Series Analysis, Wiley Blackwell, vol. 9(1), pages 1-10, January.
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