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Recursive Relations for Multistep Prediction of a Stationary Time Series

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  • Pascal Bondon

Abstract

Recursive relations are established between the coefficients of the finite past multistep linear predictors of a stationary time series. These relations generalize known results when the prediction is based on infinite past and permit simplification of the numerical calculation of the finite past predictors.

Suggested Citation

  • Pascal Bondon, 2001. "Recursive Relations for Multistep Prediction of a Stationary Time Series," Journal of Time Series Analysis, Wiley Blackwell, vol. 22(4), pages 399-410, July.
    • Handle: RePEc:bla:jtsera:v:22:y:2001:i:4:p:399-410
    DOI: 10.1111/1467-9892.00232
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    Cited by:

    1. Proietti, Tommaso, 2011. "Direct and iterated multistep AR methods for difference stationary processes," International Journal of Forecasting, Elsevier, vol. 27(2), pages 266-280.
    2. Tommaso Proietti, 2016. "The Multistep Beveridge--Nelson Decomposition," Econometric Reviews, Taylor & Francis Journals, vol. 35(3), pages 373-395, March.
    3. Benassi Romain & Pievatolo Antonio & Göb Rainer, 2010. "An L-Banded Approximation to the Inverse of Symmetric Toeplitz Matrices," Stochastics and Quality Control, De Gruyter, vol. 25(1), pages 13-30, January.
    4. Shaman, Paul, 2010. "Generalized Levinson-Durbin sequences, binomial coefficients and autoregressive estimation," Journal of Multivariate Analysis, Elsevier, vol. 101(5), pages 1263-1273, May.
    5. Palma, Wilfredo & Bondon, Pascal & Tapia, José, 2008. "Assessing influence in Gaussian long-memory models," Computational Statistics & Data Analysis, Elsevier, vol. 52(9), pages 4487-4501, May.

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