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Least-squares estimation and ANOVA for periodic autoregressive time series

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  • Shao, Q.
  • Ni, P.P.

Abstract

The periodic correlation exists throughout the whole process in a analysis of variance (ANOVA) type model where the error terms consist of a periodic autoregressive time series. This paper studies the asymptotic property of least-squares estimators and linear testable hypotheses with a modified F-test in the analysis of variance akin to periodic autoregressive series. The techniques are applied in making inference on the quarterly streamflow in Asotin, WA.

Suggested Citation

  • Shao, Q. & Ni, P.P., 2004. "Least-squares estimation and ANOVA for periodic autoregressive time series," Statistics & Probability Letters, Elsevier, vol. 69(3), pages 287-297, September.
  • Handle: RePEc:eee:stapro:v:69:y:2004:i:3:p:287-297
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    References listed on IDEAS

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    1. QIN SHAO & ROBERT Lund, 2004. "Computation and Characterization of Autocorrelations and Partial Autocorrelations in Periodic ARMA Models," Journal of Time Series Analysis, Wiley Blackwell, vol. 25(3), pages 359-372, May.
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    Cited by:

    1. Sarnaglia, A.J.Q. & Reisen, V.A. & Lévy-Leduc, C., 2010. "Robust estimation of periodic autoregressive processes in the presence of additive outliers," Journal of Multivariate Analysis, Elsevier, vol. 101(9), pages 2168-2183, October.
    2. Annie Tubadji & Vassilis Angelis & Peter Nijkamp, 2014. "Local culture and resistance to shocks in economic forecasts: a case study of Greece," Economics and Business Letters, Oviedo University Press, vol. 3(4), pages 298-308.

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